{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,27]],"date-time":"2026-08-27T15:24:05Z","timestamp":1787844245977,"version":"build-2784847793"},"publisher-location":"New York, NY, USA","reference-count":141,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,10,25]],"date-time":"2021-10-25T00:00:00Z","timestamp":1635120000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,10,25]]},"DOI":"10.1145\/3447993.3483273","type":"proceedings-article","created":{"date-parts":[[2021,10,26]],"date-time":"2021-10-26T09:00:31Z","timestamp":1635238831000},"page":"789-803","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":18,"title":["Visage"],"prefix":"10.1145","author":[{"given":"Sagar","family":"Jha","sequence":"first","affiliation":[{"name":"Microsoft"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Youjie","family":"Li","sequence":"additional","affiliation":[{"name":"Microsoft"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shadi","family":"Noghabi","sequence":"additional","affiliation":[{"name":"Microsoft"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vaishnavi","family":"Ranganathan","sequence":"additional","affiliation":[{"name":"Microsoft"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peeyush","family":"Kumar","sequence":"additional","affiliation":[{"name":"Microsoft"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew","family":"Nelson","sequence":"additional","affiliation":[{"name":"Microsoft"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael","family":"Toelle","sequence":"additional","affiliation":[{"name":"Microsoft"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sudipta","family":"Sinha","sequence":"additional","affiliation":[{"name":"Microsoft"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ranveer","family":"Chandra","sequence":"additional","affiliation":[{"name":"Microsoft"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anirudh","family":"Badam","sequence":"additional","affiliation":[{"name":"Microsoft"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2021,10,25]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00031"},{"key":"e_1_3_2_1_2_1","volume-title":"17th USENIX Symposium on Networked Systems Design and Implementation (NSDI 20)","author":"Ahmad Fawad","year":"2020","unstructured":"Fawad Ahmad , Hang Qiu , Ray Eells , Fan Bai , and Ramesh Govindan . 2020 . CarMap: Fast 3D Feature Map Updates for Automobiles . In 17th USENIX Symposium on Networked Systems Design and Implementation (NSDI 20) . USENIX Association, Santa Clara, CA, 1063--1081. https:\/\/www.usenix.org\/conference\/nsdi20\/presentation\/ahmad Fawad Ahmad, Hang Qiu, Ray Eells, Fan Bai, and Ramesh Govindan. 2020. CarMap: Fast 3D Feature Map Updates for Automobiles. In 17th USENIX Symposium on Networked Systems Design and Implementation (NSDI 20). USENIX Association, Santa Clara, CA, 1063--1081. https:\/\/www.usenix.org\/conference\/nsdi20\/presentation\/ahmad"},{"key":"e_1_3_2_1_3_1","unstructured":"Microsoft AirSim. https:\/\/github.com\/microsoft\/AirSim.  Microsoft AirSim. https:\/\/github.com\/microsoft\/AirSim."},{"key":"e_1_3_2_1_4_1","unstructured":"Alliance for Open Media Video 1 Codec. https:\/\/aomedia.org\/av1-features\/.  Alliance for Open Media Video 1 Codec. https:\/\/aomedia.org\/av1-features\/."},{"key":"e_1_3_2_1_5_1","unstructured":"Allow priority settings for files being uploaded. https:\/\/onedrive.uservoice.com\/forums\/913522-onedrive-on-windows\/suggestions\/6802608-allow-priority-settings-for-files-being-uploaded.  Allow priority settings for files being uploaded. https:\/\/onedrive.uservoice.com\/forums\/913522-onedrive-on-windows\/suggestions\/6802608-allow-priority-settings-for-files-being-uploaded."},{"key":"e_1_3_2_1_6_1","unstructured":"Ganesh Ananthanarayanan Yuanchao Shu Landon Cox and Victor Bahl. Microsoft-Rocket-Video-Analytics-Platform https:\/\/github.com\/microsoft\/Microsoft-Rocket-Video-Analytics-Platform.  Ganesh Ananthanarayanan Yuanchao Shu Landon Cox and Victor Bahl. Microsoft-Rocket-Video-Analytics-Platform https:\/\/github.com\/microsoft\/Microsoft-Rocket-Video-Analytics-Platform."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/34.67633"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2017.09.040"},{"key":"e_1_3_2_1_9_1","volume-title":"BSCGAN: Deep Background Subtraction with Conditional Generative Adversarial Networks. In 2018 25th IEEE International Conference on Image Processing (ICIP). IEEE, 4018--4022","author":"Bakkay Mohammed Chafik","year":"2018","unstructured":"Mohammed Chafik Bakkay , Hatem A Rashwan , Houssam Salmane , Louahdi Khoudour , D Puigtt , and Yassine Ruichek . 2018 . BSCGAN: Deep Background Subtraction with Conditional Generative Adversarial Networks. In 2018 25th IEEE International Conference on Image Processing (ICIP). IEEE, 4018--4022 . Mohammed Chafik Bakkay, Hatem A Rashwan, Houssam Salmane, Louahdi Khoudour, D Puigtt, and Yassine Ruichek. 2018. BSCGAN: Deep Background Subtraction with Conditional Generative Adversarial Networks. In 2018 25th IEEE International Conference on Image Processing (ICIP). IEEE, 4018--4022."},{"key":"e_1_3_2_1_10_1","volume-title":"5th International Conference on Learning Representations, ICLR","author":"Ball\u00e9 Johannes","year":"2019","unstructured":"Johannes Ball\u00e9 , Valero Laparra , and Eero Simoncelli . 2019 . End-to-end optimized image compression . In 5th International Conference on Learning Representations, ICLR 2017. Johannes Ball\u00e9, Valero Laparra, and Eero Simoncelli. 2019. End-to-end optimized image compression. In 5th International Conference on Learning Representations, ICLR 2017."},{"key":"e_1_3_2_1_11_1","unstructured":"Drone Base. How Drones Are Supporting Renewable Energy. https:\/\/blog.dronebase.com\/how-drones-are-supporting-renewable-energy.  Drone Base. How Drones Are Supporting Renewable Energy. https:\/\/blog.dronebase.com\/how-drones-are-supporting-renewable-energy."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3318464.3389692"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICACCI.2014.6968643"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3386901.3389033"},{"key":"e_1_3_2_1_15_1","unstructured":"Bentley Systems for Maintenance Inspections. https:\/\/www.bentley.com\/en\/solutions\/transportation-inspection.  Bentley Systems for Maintenance Inspections. https:\/\/www.bentley.com\/en\/solutions\/transportation-inspection."},{"key":"e_1_3_2_1_16_1","volume-title":"Dulloor","author":"Canel Christopher","year":"2019","unstructured":"Christopher Canel , Thomas Kim , Giulio Zhou , Conglong Li , Hyeontaek Lim , David G. Andersen , Michael Kaminsky , and Subramanya R . Dulloor . 2019 . Scaling Video Analytics on Constrained Edge Nodes. In arXiv, cs.CV, 1905.13536. arXiv:cs.CV\/1905.13536 Christopher Canel, Thomas Kim, Giulio Zhou, Conglong Li, Hyeontaek Lim, David G. Andersen, Michael Kaminsky, and Subramanya R. Dulloor. 2019. Scaling Video Analytics on Constrained Edge Nodes. In arXiv, cs.CV, 1905.13536. arXiv:cs.CV\/1905.13536"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/2809695.2809711"},{"key":"e_1_3_2_1_18_1","unstructured":"UAV Coach. Agricultural Drones: How Drones Are Revolutionizing Agriculture and How to Break into this Booming Market. https:\/\/uavcoach.com\/agricultural-drones\/.  UAV Coach. Agricultural Drones: How Drones Are Revolutionizing Agriculture and How to Break into this Booming Market. https:\/\/uavcoach.com\/agricultural-drones\/."},{"key":"e_1_3_2_1_19_1","unstructured":"Federal Communications Commission. 2020 Broadband Deployment Report. https:\/\/docs.fcc.gov\/public\/attachments\/FCC-20-50A1.pdf.  Federal Communications Commission. 2020 Broadband Deployment Report. https:\/\/docs.fcc.gov\/public\/attachments\/FCC-20-50A1.pdf."},{"key":"e_1_3_2_1_20_1","unstructured":"Resilio Connect. Job Priority. https:\/\/connect.resilio.com\/hc\/en-us\/articles\/360000006084-Job-priority-.  Resilio Connect. Job Priority. https:\/\/connect.resilio.com\/hc\/en-us\/articles\/360000006084-Job-priority-."},{"key":"e_1_3_2_1_21_1","unstructured":"DroneDeploy For Construction. https:\/\/www.dronedeploy.com\/solutions\/construction\/.  DroneDeploy For Construction. https:\/\/www.dronedeploy.com\/solutions\/construction\/."},{"key":"e_1_3_2_1_22_1","unstructured":"CropQuest Precision Agriculture Data. https:\/\/www.cropquest.com\/precision-ag-drone-images-big-data\/.  CropQuest Precision Agriculture Data. https:\/\/www.cropquest.com\/precision-ag-drone-images-big-data\/."},{"key":"e_1_3_2_1_23_1","unstructured":"University of Washington CSE455. Features and Image Matching. https:\/\/courses.cs.washington.edu\/courses\/cse455\/09wi\/Lects\/lect6.pdf.  University of Washington CSE455. Features and Image Matching. https:\/\/courses.cs.washington.edu\/courses\/cse455\/09wi\/Lects\/lect6.pdf."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.3390\/rs10020285"},{"key":"e_1_3_2_1_25_1","unstructured":"Biplob Debnath Sudipta Sengupta and Jin Li. 2010. ChunkStash: Speeding up Inline Storage Deduplication using Flash Memory. In 2010 USENIX Annual Technical Conference (ATC) (2010 usenix annual technical conference (atc) ed.). USENIX. https:\/\/www.microsoft.com\/en-us\/research\/publication\/chunkstash-speeding-up-inline-storage-deduplication-using-flash-memory\/  Biplob Debnath Sudipta Sengupta and Jin Li. 2010. ChunkStash: Speeding up Inline Storage Deduplication using Flash Memory. In 2010 USENIX Annual Technical Conference (ATC) (2010 usenix annual technical conference (atc) ed.). USENIX. https:\/\/www.microsoft.com\/en-us\/research\/publication\/chunkstash-speeding-up-inline-storage-deduplication-using-flash-memory\/"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2018.00060"},{"key":"e_1_3_2_1_27_1","unstructured":"DJi Mavic 2 Mini Specs. https:\/\/www.dji.com\/mavic-mini\/specs.  DJi Mavic 2 Mini Specs. https:\/\/www.dji.com\/mavic-mini\/specs."},{"key":"e_1_3_2_1_28_1","unstructured":"DJI Recommended Overlap for Drone Imagery. https:\/\/support.pix4d.com\/hc\/en-us\/articles\/203756125-How-to-verify-that-there-is-enough-overlap-between-the-images.  DJI Recommended Overlap for Drone Imagery. https:\/\/support.pix4d.com\/hc\/en-us\/articles\/203756125-How-to-verify-that-there-is-enough-overlap-between-the-images."},{"key":"e_1_3_2_1_29_1","unstructured":"DJI Terra. https:\/\/www.dji.com\/dji-terra.  DJI Terra. https:\/\/www.dji.com\/dji-terra."},{"key":"e_1_3_2_1_30_1","unstructured":"Docker Container Environment. https:\/\/docs.docker.com\/get-started\/overview\/.  Docker Container Environment. https:\/\/docs.docker.com\/get-started\/overview\/."},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDCS.2017.94"},{"key":"e_1_3_2_1_32_1","unstructured":"DroneDeploy. Agremo Plant Count Health. https:\/\/www.dronedeploy.com\/product\/market\/nyocdrbegyikewvm\/#agremo-plant-count-health.  DroneDeploy. Agremo Plant Count Health. https:\/\/www.dronedeploy.com\/product\/market\/nyocdrbegyikewvm\/#agremo-plant-count-health."},{"key":"e_1_3_2_1_33_1","unstructured":"DroneDeploy Recommended Overlap for Drone Imagery. https:\/\/support.dronedeploy.com\/docs\/making-successful-maps.  DroneDeploy Recommended Overlap for Drone Imagery. https:\/\/support.dronedeploy.com\/docs\/making-successful-maps."},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2009.934187"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.3390\/rs70404213"},{"key":"e_1_3_2_1_36_1","unstructured":"EarthSense TerraSentia Terrestrial LiDAR Sensing. https:\/\/www.earthsense.co\/.  EarthSense TerraSentia Terrestrial LiDAR Sensing. https:\/\/www.earthsense.co\/."},{"key":"e_1_3_2_1_37_1","volume-title":"Presented as part of the 2012 USENIX Annual Technical Conference (USENIX ATC 12)","author":"El-Shimi Ahmed","unstructured":"Ahmed El-Shimi , Ran Kalach , Ankit Kumar , Adi Ottean , Jin Li , and Sudipta Sengupta . 2012. Primary Data Deduplication---Large Scale Study and System Design . In Presented as part of the 2012 USENIX Annual Technical Conference (USENIX ATC 12) . USENIX , Boston, MA , 285--296. https:\/\/www.usenix.org\/conference\/atc12\/technical-sessions\/presentation\/el-shimi Ahmed El-Shimi, Ran Kalach, Ankit Kumar, Adi Ottean, Jin Li, and Sudipta Sengupta. 2012. Primary Data Deduplication---Large Scale Study and System Design. In Presented as part of the 2012 USENIX Annual Technical Conference (USENIX ATC 12). USENIX, Boston, MA, 285--296. https:\/\/www.usenix.org\/conference\/atc12\/technical-sessions\/presentation\/el-shimi"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1109\/ESARS-ITEC.2016.7841398"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-012-9365-8"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3301293.3302365"},{"key":"e_1_3_2_1_41_1","volume-title":"A Telecom Perspective on the Internet of Drones: From LTE-Advanced to 5G. In arXiv, cs.NI","author":"Hang Cui Min Xu Yan Li","year":"1803","unstructured":"Yan Li Hang Cui Min Xu Dan Wu Henrik Ryd\u00e9n Sakib Bin Redhwan Guang Yang , Xingqin Lin . 2018. A Telecom Perspective on the Internet of Drones: From LTE-Advanced to 5G. In arXiv, cs.NI , 1803 .11048. arXiv:cs.NI\/1803.11048 Yan Li Hang Cui Min Xu Dan Wu Henrik Ryd\u00e9n Sakib Bin Redhwan Guang Yang, Xingqin Lin. 2018. A Telecom Perspective on the Internet of Drones: From LTE-Advanced to 5G. In arXiv, cs.NI, 1803.11048. arXiv:cs.NI\/1803.11048"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/3241539.3241557"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1145\/3173162.3173185"},{"key":"e_1_3_2_1_44_1","unstructured":"H.264\/AVC1: Advanced Video Coding. https:\/\/www.itu.int\/rec\/T-REC-H.264.  H.264\/AVC1: Advanced Video Coding. https:\/\/www.itu.int\/rec\/T-REC-H.264."},{"key":"e_1_3_2_1_45_1","unstructured":"H.265\/HEVC: High Efficiency Video Coding. https:\/\/www.itu.int\/rec\/T-REC-H.265.  H.265\/HEVC: High Efficiency Video Coding. https:\/\/www.itu.int\/rec\/T-REC-H.265."},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511811685"},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2015.2437998"},{"key":"e_1_3_2_1_48_1","unstructured":"Headwall Hyperspectral Remote Sensing. https:\/\/www.headwallphotonics.com\/hyperspectral-sensors.  Headwall Hyperspectral Remote Sensing. https:\/\/www.headwallphotonics.com\/hyperspectral-sensors."},{"key":"e_1_3_2_1_49_1","unstructured":"How to prioritize the upload of files. https:\/\/support.google.com\/drive\/forum\/AAAAOxCWsToJvZX4JEObwg\/?hl=fr.  How to prioritize the upload of files. https:\/\/support.google.com\/drive\/forum\/AAAAOxCWsToJvZX4JEObwg\/?hl=fr."},{"key":"e_1_3_2_1_50_1","unstructured":"How to set file syncing priority. https:\/\/help.dropbox.com\/installs-integrations\/sync-uploads\/prioritize-files-sync.  How to set file syncing priority. https:\/\/help.dropbox.com\/installs-integrations\/sync-uploads\/prioritize-files-sync."},{"key":"e_1_3_2_1_51_1","volume-title":"Focus: Querying Large Video Datasets with Low Latency and Low Cost. In 13th USENIX Symposium on Operating Systems Design and Implementation (OSDI 18)","author":"Hsieh Kevin","year":"2018","unstructured":"Kevin Hsieh , Ganesh Ananthanarayanan , Peter Bodik , Shivaram Venkataraman , Paramvir Bahl , Matthai Philipose , Phillip B. Gibbons , and Onur Mutlu . 2018 . Focus: Querying Large Video Datasets with Low Latency and Low Cost. In 13th USENIX Symposium on Operating Systems Design and Implementation (OSDI 18) . USENIX Association, Carlsbad, CA, 269--286. Kevin Hsieh, Ganesh Ananthanarayanan, Peter Bodik, Shivaram Venkataraman, Paramvir Bahl, Matthai Philipose, Phillip B. Gibbons, and Onur Mutlu. 2018. Focus: Querying Large Video Datasets with Low Latency and Low Cost. In 13th USENIX Symposium on Operating Systems Design and Implementation (OSDI 18). USENIX Association, Carlsbad, CA, 269--286."},{"key":"e_1_3_2_1_52_1","doi-asserted-by":"publisher","DOI":"10.1145\/2619239.2626296"},{"key":"e_1_3_2_1_53_1","volume-title":"Proceedings of the 2010 USENIX Conference on USENIX Annual Technical Conference (USENIXATC'10)","author":"Ihm Sunghwan","unstructured":"Sunghwan Ihm , KyoungSoo Park , and Vivek S. Pai . 2010. Wide-Area Network Acceleration for the Developing World . In Proceedings of the 2010 USENIX Conference on USENIX Annual Technical Conference (USENIXATC'10) . USENIX Association, USA, 18. Sunghwan Ihm, KyoungSoo Park, and Vivek S. Pai. 2010. Wide-Area Network Acceleration for the Developing World. In Proceedings of the 2010 USENIX Conference on USENIX Annual Technical Conference (USENIXATC'10). USENIX Association, USA, 18."},{"key":"e_1_3_2_1_54_1","unstructured":"Intel. Intel Xeon Processors https:\/\/www.intel.com\/content\/www\/us\/en\/products\/details\/processors\/xeon.html.  Intel. Intel Xeon Processors https:\/\/www.intel.com\/content\/www\/us\/en\/products\/details\/processors\/xeon.html."},{"key":"e_1_3_2_1_55_1","volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR).","author":"Isola Phillip","unstructured":"Phillip Isola , Jun-Yan Zhu , Tinghui Zhou , and Alexei A. Efros . 2017. Image-To-Image Translation With Conditional Adversarial Networks . In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A. Efros. 2017. Image-To-Image Translation With Conditional Adversarial Networks. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)."},{"key":"e_1_3_2_1_56_1","doi-asserted-by":"publisher","DOI":"10.1109\/SEC50012.2020.00016"},{"key":"e_1_3_2_1_57_1","doi-asserted-by":"publisher","DOI":"10.1145\/3230543.3230574"},{"key":"e_1_3_2_1_58_1","volume-title":"Optimizing Deep CNN-Based Queries over Video Streams at Scale. CoRR abs\/1703.02529","author":"Kang Daniel","year":"2017","unstructured":"Daniel Kang , John Emmons , Firas Abuzaid , Peter Bailis , and Matei Zaharia . 2017. Optimizing Deep CNN-Based Queries over Video Streams at Scale. CoRR abs\/1703.02529 ( 2017 ). arXiv:1703.02529 http:\/\/arxiv.org\/abs\/1703.02529 Daniel Kang, John Emmons, Firas Abuzaid, Peter Bailis, and Matei Zaharia. 2017. Optimizing Deep CNN-Based Queries over Video Streams at Scale. CoRR abs\/1703.02529 (2017). arXiv:1703.02529 http:\/\/arxiv.org\/abs\/1703.02529"},{"key":"e_1_3_2_1_59_1","doi-asserted-by":"publisher","DOI":"10.23919\/MIPRO.2019.8756696"},{"key":"e_1_3_2_1_60_1","unstructured":"Kubernetes Cluster Manager. https:\/\/kubernetes.io\/docs\/concepts\/.  Kubernetes Cluster Manager. https:\/\/kubernetes.io\/docs\/concepts\/."},{"key":"e_1_3_2_1_61_1","unstructured":"Fujitsu Laboratories. https:\/\/www.fujitsu.com\/global\/about\/resources\/news\/press-releases\/2014\/0916-01.html.  Fujitsu Laboratories. https:\/\/www.fujitsu.com\/global\/about\/resources\/news\/press-releases\/2014\/0916-01.html."},{"key":"e_1_3_2_1_62_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00339"},{"key":"e_1_3_2_1_63_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICME.2007.4284808"},{"key":"e_1_3_2_1_64_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2017.151"},{"key":"e_1_3_2_1_65_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2014.6907055"},{"key":"e_1_3_2_1_66_1","doi-asserted-by":"publisher","DOI":"10.1145\/3300061.3300116"},{"key":"e_1_3_2_1_67_1","doi-asserted-by":"publisher","DOI":"10.1145\/3356250.3360041"},{"key":"e_1_3_2_1_68_1","unstructured":"Zihao Liu Xiaowei Xu Tao Liu Qi Liu Yanzhi Wang Yiyu Shi Wujie Wen Meiping Huang Haiyun Yuan and Jian Zhuang. Machine Vision Guided 3D Medical Image Compression for Efficient Transmission and Accurate Segmentation in the Clouds. arXiv:cs.CV\/1904.08487  Zihao Liu Xiaowei Xu Tao Liu Qi Liu Yanzhi Wang Yiyu Shi Wujie Wen Meiping Huang Haiyun Yuan and Jian Zhuang. Machine Vision Guided 3D Medical Image Compression for Efficient Transmission and Accurate Segmentation in the Clouds. arXiv:cs.CV\/1904.08487"},{"key":"e_1_3_2_1_69_1","doi-asserted-by":"publisher","DOI":"10.1023\/B:VISI.0000029664.99615.94"},{"key":"e_1_3_2_1_70_1","doi-asserted-by":"publisher","DOI":"10.1177\/0309133313515293"},{"key":"e_1_3_2_1_71_1","doi-asserted-by":"publisher","DOI":"10.1145\/3098822.3098843"},{"key":"e_1_3_2_1_72_1","unstructured":"Francisco Massa and Ross Girshick. 2018. maskrcnn-benchmark: Fast modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch.  Francisco Massa and Ross Girshick. 2018. maskrcnn-benchmark: Fast modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch."},{"key":"e_1_3_2_1_73_1","doi-asserted-by":"publisher","DOI":"10.1145\/2733373.2806225"},{"key":"e_1_3_2_1_74_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01088"},{"key":"e_1_3_2_1_75_1","unstructured":"Microsoft. Azure Blob Storage https:\/\/azure.microsoft.com\/en-us\/services\/storage\/blobs\/.  Microsoft. Azure Blob Storage https:\/\/azure.microsoft.com\/en-us\/services\/storage\/blobs\/."},{"key":"e_1_3_2_1_76_1","unstructured":"Microsoft. Surface Book 2https:\/\/www.microsoft.com\/en-us\/p\/surface-book-2\/8mcpzjjcc98c?activetab=pivot%3aoverviewtab.  Microsoft. Surface Book 2https:\/\/www.microsoft.com\/en-us\/p\/surface-book-2\/8mcpzjjcc98c?activetab=pivot%3aoverviewtab."},{"key":"e_1_3_2_1_77_1","unstructured":"Mehdi Mirza and Simon Osindero. 2014. Conditional Generative Adversarial Nets. In arXiv cs.LG 1411.1784. arXiv:cs.LG\/1411.1784  Mehdi Mirza and Simon Osindero. 2014. Conditional Generative Adversarial Nets. In arXiv cs.LG 1411.1784. arXiv:cs.LG\/1411.1784"},{"key":"e_1_3_2_1_78_1","unstructured":"NetApp. NetApp Data Compression Deduplication and Data Compaction. https:\/\/www.netapp.com\/us\/media\/tr-4476.pdf.  NetApp. NetApp Data Compression Deduplication and Data Compaction. https:\/\/www.netapp.com\/us\/media\/tr-4476.pdf."},{"key":"e_1_3_2_1_79_1","unstructured":"NVIDIA. NVIDIA GeForce GTX graphics cards https:\/\/www.nvidia.com\/en-us\/geforce\/10-series\/.  NVIDIA. NVIDIA GeForce GTX graphics cards https:\/\/www.nvidia.com\/en-us\/geforce\/10-series\/."},{"key":"e_1_3_2_1_80_1","unstructured":"NVIDIA Corporation. NVIDIA TITAN RTX https:\/\/www.nvidia.com\/en-us\/titan\/titan-rtx\/.  NVIDIA Corporation. NVIDIA TITAN RTX https:\/\/www.nvidia.com\/en-us\/titan\/titan-rtx\/."},{"key":"e_1_3_2_1_81_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.264"},{"key":"e_1_3_2_1_82_1","volume-title":"A Survey on Structure from Motion. CoRR abs\/1701.08493","author":"\u00d6zyesil Onur","year":"2017","unstructured":"Onur \u00d6zyesil , Vladislav Voroninski , Ronen Basri , and Amit Singer . 2017. A Survey on Structure from Motion. CoRR abs\/1701.08493 ( 2017 ). arXiv:1701.08493 http:\/\/arxiv.org\/abs\/1701.08493 Onur \u00d6zyesil, Vladislav Voroninski, Ronen Basri, and Amit Singer. 2017. A Survey on Structure from Motion. CoRR abs\/1701.08493 (2017). arXiv:1701.08493 http:\/\/arxiv.org\/abs\/1701.08493"},{"key":"e_1_3_2_1_83_1","unstructured":"Parrot Sequoia+ Hyperspectral Drone Camera. https:\/\/www.sensefly.com\/camera\/parrot-sequoia\/.  Parrot Sequoia+ Hyperspectral Drone Camera. https:\/\/www.sensefly.com\/camera\/parrot-sequoia\/."},{"key":"e_1_3_2_1_84_1","unstructured":"Pix4D. Inspect analyze and visualize your crop changes all year round. https:\/\/www.pix4d.com\/product\/pix4dfields.  Pix4D. Inspect analyze and visualize your crop changes all year round. https:\/\/www.pix4d.com\/product\/pix4dfields."},{"key":"e_1_3_2_1_85_1","unstructured":"Pix4D. Processing Large Datasets. https:\/\/support.pix4d.com\/hc\/en-us\/articles\/202558579-Processing-Large-Datasets.  Pix4D. Processing Large Datasets. https:\/\/support.pix4d.com\/hc\/en-us\/articles\/202558579-Processing-Large-Datasets."},{"key":"e_1_3_2_1_86_1","unstructured":"Pix4D. https:\/\/www.pix4d.com\/.  Pix4D. https:\/\/www.pix4d.com\/."},{"key":"e_1_3_2_1_87_1","unstructured":"Pix4D Recommended Overlap for Drone Imagery. https:\/\/support.pix4d.com\/hc\/en-us\/articles\/203756125-How-to-verify-that-there-is-enough-overlap-between-the-images.  Pix4D Recommended Overlap for Drone Imagery. https:\/\/support.pix4d.com\/hc\/en-us\/articles\/203756125-How-to-verify-that-there-is-enough-overlap-between-the-images."},{"key":"e_1_3_2_1_88_1","unstructured":"Portable Network Graphics (PNG). http:\/\/libpng.org\/pub\/png\/libpng.html.  Portable Network Graphics (PNG). http:\/\/libpng.org\/pub\/png\/libpng.html."},{"key":"e_1_3_2_1_89_1","unstructured":"PostGIS: A Geospatial Information Services Engine for PostgreSQL. https:\/\/postgis.net\/.  PostGIS: A Geospatial Information Services Engine for PostgreSQL. https:\/\/postgis.net\/."},{"key":"e_1_3_2_1_90_1","unstructured":"PostGIS: Geometries. http:\/\/postgis.net\/workshops\/postgis-intro\/geometries.html.  PostGIS: Geometries. http:\/\/postgis.net\/workshops\/postgis-intro\/geometries.html."},{"key":"e_1_3_2_1_91_1","unstructured":"PostGIS Polygon Query Performance Profiling. https:\/\/carto.com\/blog\/postgis-performance\/.  PostGIS Polygon Query Performance Profiling. https:\/\/carto.com\/blog\/postgis-performance\/."},{"key":"e_1_3_2_1_92_1","unstructured":"PostGIS ST Intersection Optimization. https:\/\/www.r-spatial.org\/r\/2017\/06\/22\/spatial-index.html.  PostGIS ST Intersection Optimization. https:\/\/www.r-spatial.org\/r\/2017\/06\/22\/spatial-index.html."},{"key":"e_1_3_2_1_93_1","unstructured":"NORTH POWDER. https:\/\/northpowder.com\/.  NORTH POWDER. https:\/\/northpowder.com\/."},{"key":"e_1_3_2_1_94_1","unstructured":"PrecisionAg. Big Data Big Crops? How Ag Can Harness the Power of Satellites and the Cloud. https:\/\/www.precisionag.com\/digital-farming\/big-data-big-crops-how-ag-can-harness-the-power-of-satellites-and-the-cloud\/.  PrecisionAg. Big Data Big Crops? How Ag Can Harness the Power of Satellites and the Cloud. https:\/\/www.precisionag.com\/digital-farming\/big-data-big-crops-how-ag-can-harness-the-power-of-satellites-and-the-cloud\/."},{"key":"e_1_3_2_1_95_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0923-5965(01)00024-8"},{"key":"e_1_3_2_1_96_1","unstructured":"Alec Radford Luke Metz and Soumith Chintala. 2015. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks. In arXiv cs.LG 1511.06434. arXiv:cs.LG\/1511.06434  Alec Radford Luke Metz and Soumith Chintala. 2015. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks. In arXiv cs.LG 1511.06434. arXiv:cs.LG\/1511.06434"},{"key":"e_1_3_2_1_97_1","unstructured":"Railroads continue to tap drone technology to inspect track bridges. https:\/\/www.progressiverailroading.com\/mow\/article\/Railroads-continue-to-tap-drone-technology-to-inspect-track-bridges-57270.  Railroads continue to tap drone technology to inspect track bridges. https:\/\/www.progressiverailroading.com\/mow\/article\/Railroads-continue-to-tap-drone-technology-to-inspect-track-bridges-57270."},{"key":"e_1_3_2_1_98_1","unstructured":"Real-time Aerial Mapping with a GPU Cluster.  Real-time Aerial Mapping with a GPU Cluster."},{"key":"e_1_3_2_1_99_1","volume-title":"Proceedings of the 34th International Conference on Machine Learning (Proceedings of Machine Learning Research), Doina Precup and Yee Whye Teh (Eds.)","volume":"70","author":"Rippel Oren","year":"2017","unstructured":"Oren Rippel and Lubomir Bourdev . 2017 . Real-Time Adaptive Image Compression . In Proceedings of the 34th International Conference on Machine Learning (Proceedings of Machine Learning Research), Doina Precup and Yee Whye Teh (Eds.) , Vol. 70 . International Convention Centre, Sydney, Australia, 2922--2930. Oren Rippel and Lubomir Bourdev. 2017. Real-Time Adaptive Image Compression. In Proceedings of the 34th International Conference on Machine Learning (Proceedings of Machine Learning Research), Doina Precup and Yee Whye Teh (Eds.), Vol. 70. International Convention Centre, Sydney, Australia, 2922--2930."},{"key":"e_1_3_2_1_100_1","unstructured":"riverbed. https:\/\/www.riverbed.com\/products\/steelhead\/steelhead-sd-wan.html.  riverbed. https:\/\/www.riverbed.com\/products\/steelhead\/steelhead-sd-wan.html."},{"key":"e_1_3_2_1_101_1","volume-title":"Compressed Video Communications","author":"Sadka Abdul H.","unstructured":"Abdul H. Sadka . 2002. Compressed Video Communications . Wiley . Abdul H. Sadka. 2002. Compressed Video Communications. Wiley."},{"key":"e_1_3_2_1_102_1","doi-asserted-by":"publisher","DOI":"10.5555\/3157096.3157346"},{"key":"e_1_3_2_1_103_1","doi-asserted-by":"crossref","unstructured":"Mark Sandler Andrew Howard Menglong Zhu Andrey Zhmoginov and Liang-Chieh Chen. 2018. MobileNetV2: Inverted Residuals and Linear Bottlenecks. arXiv:cs.CV\/1801.04381  Mark Sandler Andrew Howard Menglong Zhu Andrey Zhmoginov and Liang-Chieh Chen. 2018. MobileNetV2: Inverted Residuals and Linear Bottlenecks. arXiv:cs.CV\/1801.04381","DOI":"10.1109\/CVPR.2018.00474"},{"key":"e_1_3_2_1_104_1","doi-asserted-by":"publisher","DOI":"10.1109\/12.54838"},{"key":"e_1_3_2_1_105_1","unstructured":"Citrix SD-WAN. https:\/\/www.citrix.com\/products\/citrix-sd-wan\/.  Citrix SD-WAN. https:\/\/www.citrix.com\/products\/citrix-sd-wan\/."},{"key":"e_1_3_2_1_106_1","unstructured":"Set sync priority on a per-folder basis. https:\/\/forum.odrive.com\/t\/set-sync-priority-on-a-per-folder-basis\/636.  Set sync priority on a per-folder basis. https:\/\/forum.odrive.com\/t\/set-sync-priority-on-a-per-folder-basis\/636."},{"key":"e_1_3_2_1_107_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.autcon.2014.01.004"},{"key":"e_1_3_2_1_108_1","article-title":"Applications of Remote Sensing in Precision Agriculture","volume":"12","author":"Sishodia Rajendra P.","year":"2020","unstructured":"Rajendra P. Sishodia , Ram L. Ray , and Sudhir K. Singh . 2020 . Applications of Remote Sensing in Precision Agriculture : A Review. Remote Sensing 12 , 19 (2020). https:\/\/www.mdpi.com\/2072-4292\/12\/19\/3136 Rajendra P. Sishodia, Ram L. Ray, and Sudhir K. Singh. 2020. Applications of Remote Sensing in Precision Agriculture: A Review. Remote Sensing 12, 19 (2020). https:\/\/www.mdpi.com\/2072-4292\/12\/19\/3136","journal-title":"A Review. Remote Sensing"},{"key":"e_1_3_2_1_109_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2005.861296"},{"key":"e_1_3_2_1_110_1","doi-asserted-by":"publisher","DOI":"10.1145\/2934872.2934898"},{"key":"e_1_3_2_1_111_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11676-015-0088-y"},{"key":"e_1_3_2_1_112_1","volume-title":"Lossy Image Compression with Compressive Autoencoders. In International Conference on Learning Representations. https:\/\/openreview.net\/pdf?id=rJiNwv9gg","author":"Theis L.","unstructured":"L. Theis , W. Shi , A. Cunningham , and F. Husz\u00e1r . 2017 . Lossy Image Compression with Compressive Autoencoders. In International Conference on Learning Representations. https:\/\/openreview.net\/pdf?id=rJiNwv9gg L. Theis, W. Shi, A. Cunningham, and F. Husz\u00e1r. 2017. Lossy Image Compression with Compressive Autoencoders. In International Conference on Learning Representations. https:\/\/openreview.net\/pdf?id=rJiNwv9gg"},{"key":"e_1_3_2_1_113_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2005.860338"},{"key":"e_1_3_2_1_114_1","unstructured":"Achieving Storage Efficiency through EMC Celerra Data Deduplication. https:\/\/www.dell.com\/community\/s\/vjauj58549\/attachments\/vjauj58549\/celerra\/660\/1\/h6065-achieve-storage-effficiency-celerra-dedup-wp.pdf.  Achieving Storage Efficiency through EMC Celerra Data Deduplication. https:\/\/www.dell.com\/community\/s\/vjauj58549\/attachments\/vjauj58549\/celerra\/660\/1\/h6065-achieve-storage-effficiency-celerra-dedup-wp.pdf."},{"key":"e_1_3_2_1_115_1","volume-title":"Damien Vincent, David Minnen, Shumeet Baluja, Michele Covell, and Rahul Sukthankar.","author":"Toderici George","year":"2015","unstructured":"George Toderici , Sean M. O'Malley , Sung Jin Hwang , Damien Vincent, David Minnen, Shumeet Baluja, Michele Covell, and Rahul Sukthankar. 2015 . Variable Rate Image Compression with Recurrent Neural Networks. In arXiv, cs.CV, 1511.06085. arXiv:cs.CV\/1511.06085 George Toderici, Sean M. O'Malley, Sung Jin Hwang, Damien Vincent, David Minnen, Shumeet Baluja, Michele Covell, and Rahul Sukthankar. 2015. Variable Rate Image Compression with Recurrent Neural Networks. In arXiv, cs.CV, 1511.06085. arXiv:cs.CV\/1511.06085"},{"key":"e_1_3_2_1_116_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.577"},{"key":"e_1_3_2_1_117_1","unstructured":"DOT\n  : Data-Oriented Transfer. http:\/\/www.cs.cmu.edu\/~dot-project\/.  DOT: Data-Oriented Transfer. http:\/\/www.cs.cmu.edu\/~dot-project\/."},{"key":"e_1_3_2_1_118_1","volume-title":"Fitzgibbon","author":"Triggs Bill","year":"2000","unstructured":"Bill Triggs , Philip F. McLauchlan , Richard I. Hartley , and Andrew W . Fitzgibbon . 2000 . Bundle Adjustment --- A Modern Synthesis. In Vision Algorithms: Theory and Practice, Bill Triggs, Andrew Zisserman, and Richard Szeliski (Eds.). Springer Berlin Heidelberg , Berlin, Heidelberg, 298--372. Bill Triggs, Philip F. McLauchlan, Richard I. Hartley, and Andrew W. Fitzgibbon. 2000. Bundle Adjustment --- A Modern Synthesis. In Vision Algorithms: Theory and Practice, Bill Triggs, Andrew Zisserman, and Richard Szeliski (Eds.). Springer Berlin Heidelberg, Berlin, Heidelberg, 298--372."},{"key":"e_1_3_2_1_119_1","unstructured":"Aaron Van den Oord Nal Kalchbrenner Lasse Espeholt Oriol Vinyals Alex Graves etal 2016. Conditional image generation with pixelcnn decoders. In Advances in neural information processing systems. 4790--4798.  Aaron Van den Oord Nal Kalchbrenner Lasse Espeholt Oriol Vinyals Alex Graves et al. 2016. Conditional image generation with pixelcnn decoders. In Advances in neural information processing systems. 4790--4798."},{"key":"e_1_3_2_1_120_1","doi-asserted-by":"publisher","DOI":"10.1109\/30.125072"},{"key":"e_1_3_2_1_121_1","unstructured":"Jingdong Wang Ke Sun Tianheng Cheng Borui Jiang Chaorui Deng Yang Zhao Dong Liu Yadong Mu Mingkui Tan Xinggang Wang etal 2020. Deep high-resolution representation learning for visual recognition. IEEE transactions on pattern analysis and machine intelligence (2020).  Jingdong Wang Ke Sun Tianheng Cheng Borui Jiang Chaorui Deng Yang Zhao Dong Liu Yadong Mu Mingkui Tan Xinggang Wang et al. 2020. Deep high-resolution representation learning for visual recognition. IEEE transactions on pattern analysis and machine intelligence (2020)."},{"key":"e_1_3_2_1_122_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46493-0_20"},{"key":"e_1_3_2_1_123_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2010.2092435"},{"key":"e_1_3_2_1_124_1","volume-title":"Computer Vision and Pattern Recognition (computer vision and pattern recognition ed.)","author":"Winder Simon","unstructured":"Simon Winder , Gang Hua , and Matthew Brown . 2009. Picking the Best Daisy . In Computer Vision and Pattern Recognition (computer vision and pattern recognition ed.) . IEEE Computer Society . https:\/\/www.microsoft.com\/en-us\/research\/publication\/picking-the-best-daisy\/ Simon Winder, Gang Hua, and Matthew Brown. 2009. Picking the Best Daisy. In Computer Vision and Pattern Recognition (computer vision and pattern recognition ed.). IEEE Computer Society. https:\/\/www.microsoft.com\/en-us\/research\/publication\/picking-the-best-daisy\/"},{"key":"e_1_3_2_1_125_1","unstructured":"WJE. Utilizing Drones to Assess and Maintain Your Structure's Integrity. https:\/\/www.wje.com\/knowledge\/webinars\/detail\/utilizing-drones-to-assess-and-maintain-your-structures-integrity.  WJE. Utilizing Drones to Assess and Maintain Your Structure's Integrity. https:\/\/www.wje.com\/knowledge\/webinars\/detail\/utilizing-drones-to-assess-and-maintain-your-structures-integrity."},{"key":"e_1_3_2_1_126_1","doi-asserted-by":"publisher","DOI":"10.1109\/3DV.2013.25"},{"key":"e_1_3_2_1_127_1","doi-asserted-by":"publisher","DOI":"10.1145\/3300061.3345448"},{"key":"e_1_3_2_1_128_1","doi-asserted-by":"publisher","DOI":"10.1145\/3241539.3241563"},{"key":"e_1_3_2_1_129_1","volume-title":"13th {USENIX} Symposium on Operating Systems Design and Implementation ({OSDI} 18). 645--661.","author":"Yeo Hyunho","unstructured":"Hyunho Yeo , Youngmok Jung , Jaehong Kim , Jinwoo Shin , and Dongsu Han . 2018. Neural Adaptive Content-Aware Internet Video Delivery . In 13th {USENIX} Symposium on Operating Systems Design and Implementation ({OSDI} 18). 645--661. Hyunho Yeo, Youngmok Jung, Jaehong Kim, Jinwoo Shin, and Dongsu Han. 2018. Neural Adaptive Content-Aware Internet Video Delivery. In 13th {USENIX} Symposium on Operating Systems Design and Implementation ({OSDI} 18). 645--661."},{"key":"e_1_3_2_1_130_1","doi-asserted-by":"publisher","DOI":"10.1145\/3230543.3230554"},{"key":"e_1_3_2_1_131_1","volume-title":"14th USENIX Symposium on Networked Systems Design and Implementation (NSDI 17)","author":"Zhang Haoyu","unstructured":"Haoyu Zhang , Ganesh Ananthanarayanan , Peter Bodik , Matthai Philipose , Paramvir Bahl , and Michael J. Freedman . 2017. Live Video Analytics at Scale with Approximation and Delay-Tolerance . In 14th USENIX Symposium on Networked Systems Design and Implementation (NSDI 17) . USENIX Association, Boston, MA, 377--392. Haoyu Zhang, Ganesh Ananthanarayanan, Peter Bodik, Matthai Philipose, Paramvir Bahl, and Michael J. Freedman. 2017. Live Video Analytics at Scale with Approximation and Delay-Tolerance. In 14th USENIX Symposium on Networked Systems Design and Implementation (NSDI 17). USENIX Association, Boston, MA, 377--392."},{"key":"e_1_3_2_1_132_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46487-9_40"},{"key":"e_1_3_2_1_133_1","doi-asserted-by":"publisher","DOI":"10.1145\/2789168.2790123"},{"key":"e_1_3_2_1_134_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.660"},{"key":"e_1_3_2_1_135_1","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2007.4399459"},{"key":"e_1_3_2_1_136_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.544"},{"key":"e_1_3_2_1_137_1","unstructured":"Bolei Zhou Hang Zhao Xavier Puig Tete Xiao Sanja Fidler Adela Barriuso and Antonio Torralba. Semantic Segmentation on MIT ADE20K dataset in PyTorch https:\/\/github.com\/CSAILVision\/semantic-segmentation-pytorch.  Bolei Zhou Hang Zhao Xavier Puig Tete Xiao Sanja Fidler Adela Barriuso and Antonio Torralba. Semantic Segmentation on MIT ADE20K dataset in PyTorch https:\/\/github.com\/CSAILVision\/semantic-segmentation-pytorch."},{"key":"e_1_3_2_1_138_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2003.819861"},{"key":"e_1_3_2_1_139_1","doi-asserted-by":"publisher","DOI":"10.5555\/1364813.1364831"},{"key":"e_1_3_2_1_140_1","doi-asserted-by":"publisher","DOI":"10.1109\/ISCA.2018.00052"},{"key":"e_1_3_2_1_141_1","unstructured":"ZoneMinder. https:\/\/zoneminder.com\/features\/.  ZoneMinder. https:\/\/zoneminder.com\/features\/."}],"event":{"name":"ACM MobiCom '21: The 27th Annual International Conference on Mobile Computing and Networking","location":"New Orleans Louisiana","acronym":"ACM MobiCom '21","sponsor":["SIGMOBILE ACM Special Interest Group on Mobility of Systems, Users, Data and Computing"]},"container-title":["Proceedings of the 27th Annual International Conference on Mobile Computing and Networking"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3447993.3483273","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3447993.3483273","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:49:12Z","timestamp":1750193352000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3447993.3483273"}},"subtitle":["enabling timely analytics for drone imagery"],"short-title":[],"issued":{"date-parts":[[2021,10,25]]},"references-count":141,"alternative-id":["10.1145\/3447993.3483273","10.1145\/3447993"],"URL":"https:\/\/doi.org\/10.1145\/3447993.3483273","relation":{},"subject":[],"published":{"date-parts":[[2021,10,25]]},"assertion":[{"value":"2021-10-25","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}