{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T17:32:52Z","timestamp":1775842372306,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":22,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,7,10]],"date-time":"2023-07-10T00:00:00Z","timestamp":1688947200000},"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":[[2023,7,10]]},"DOI":"10.1145\/3594556.3594619","type":"proceedings-article","created":{"date-parts":[[2023,9,12]],"date-time":"2023-09-12T21:34:46Z","timestamp":1694554486000},"page":"140-144","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["Fruits Detections Using Single Shot MultiBox Detector"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8945-3230","authenticated-orcid":false,"given":"Md","family":"Ali","sequence":"first","affiliation":[{"name":"Rider University, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-9916-8661","authenticated-orcid":false,"given":"Chris","family":"Keller","sequence":"additional","affiliation":[{"name":"Rider University, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-7523-6838","authenticated-orcid":false,"given":"Michael","family":"Huang","sequence":"additional","affiliation":[{"name":"Rider University, USA"}]}],"member":"320","published-online":{"date-parts":[[2023,9,12]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1126\/science.aaa8415"},{"key":"#cr-split#-e_1_3_2_1_2_1.1","doi-asserted-by":"crossref","unstructured":"Yann LeCun Yoshua Bengio and Geoffrey Hinton. 2015. Deep learning. nature. 521 (7553) 436-444. DOI= https:\/\/doi.org\/10.1038\/nature14539 10.1038\/nature14539","DOI":"10.1038\/nature14539"},{"key":"#cr-split#-e_1_3_2_1_2_1.2","doi-asserted-by":"crossref","unstructured":"Yann LeCun Yoshua Bengio and Geoffrey Hinton. 2015. Deep learning. nature. 521 (7553) 436-444. DOI= https:\/\/doi.org\/10.1038\/nature14539","DOI":"10.1038\/nature14539"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2023.3238524"},{"key":"e_1_3_2_1_4_1","volume-title":"Application of deep learning for object detection. Procedia computer science. (Jan","author":"Pathak Ajeet Ram","year":"2018","unstructured":"Ajeet Ram Pathak , Manjusha Pandey , and Siddharth Rautaray . 2018. Application of deep learning for object detection. Procedia computer science. (Jan 2018 ), 132:1706-17. DOI= https:\/\/doi.org\/10.1016\/j.procs.2018.05.144 10.1016\/j.procs.2018.05.144 Ajeet Ram Pathak, Manjusha Pandey, and Siddharth Rautaray. 2018. Application of deep learning for object detection. Procedia computer science. (Jan 2018), 132:1706-17. DOI= https:\/\/doi.org\/10.1016\/j.procs.2018.05.144"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-020-01316-z"},{"key":"e_1_3_2_1_6_1","volume-title":"Fruit recognition from images using deep learning. arXiv preprint arXiv:1712.00580","author":"Mure\u015fan Horea","year":"2017","unstructured":"Horea Mure\u015fan , and Mihai Oltean . 2017. Fruit recognition from images using deep learning. arXiv preprint arXiv:1712.00580 . Dec 2017 . DOI= https:\/\/doi.org\/10.48550\/arXiv.1712.00580. 10.48550\/arXiv.1712.00580 Horea Mure\u015fan, and Mihai Oltean. 2017. Fruit recognition from images using deep learning. arXiv preprint arXiv:1712.00580. Dec 2017. DOI= https:\/\/doi.org\/10.48550\/arXiv.1712.00580."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2017.7989417"},{"key":"e_1_3_2_1_8_1","volume-title":"Deepfruits: A fruit detection system using deep neural networks. sensors. (Aug","author":"Sa Inkyu","year":"2016","unstructured":"Inkyu Sa , Zongyuan Ge , Feras Dayoub , Ben Upcroft , Tristan Perez , and Chris McCool .. 2016 . Deepfruits: A fruit detection system using deep neural networks. sensors. (Aug 2016), 16(8):1222. DOI= https:\/\/doi.org\/10.3390\/s16081222 10.3390\/s16081222 Inkyu Sa, Zongyuan Ge, Feras Dayoub, Ben Upcroft, Tristan Perez, and Chris McCool.. 2016. Deepfruits: A fruit detection system using deep neural networks. sensors. (Aug 2016), 16(8):1222. DOI= https:\/\/doi.org\/10.3390\/s16081222"},{"key":"e_1_3_2_1_9_1","first-page":"1","volume-title":"International Journal of Image, Graphics and Signal Processing. (Aug 2019) ,11(8)","author":"Khan Rafflesia","unstructured":"Rafflesia Khan , and Rameswar Debnath . 2019. Multi class fruit classification using efficient object detection and recognition techniques . International Journal of Image, Graphics and Signal Processing. (Aug 2019) ,11(8) , p. 1 . DOI= 10.5815\/ijigsp.2019.08.01 Rafflesia Khan, and Rameswar Debnath. 2019. Multi class fruit classification using efficient object detection and recognition techniques. International Journal of Image, Graphics and Signal Processing. (Aug 2019) ,11(8), p.1. DOI= 10.5815\/ijigsp.2019.08.01"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCSNT.2017.8343709"},{"key":"e_1_3_2_1_11_1","first-page":"1305","volume-title":"2018 International Conference on inventive research in computing applications (ICIRCA).","author":"Jain Ayush","year":"2018","unstructured":"Chandan, Ayush Jain , and Harsh Jain . 2018 , July. Real time object detection and tracking using Deep Learning and OpenCV . In 2018 International Conference on inventive research in computing applications (ICIRCA). Jul 2018, pp. 1305 - 1308 . IEEE. DOI= 10.1109\/ICIRCA.2018.8597266 Chandan, Ayush Jain, and Harsh Jain. 2018, July. Real time object detection and tracking using Deep Learning and OpenCV. In 2018 International Conference on inventive research in computing applications (ICIRCA). Jul 2018, pp. 1305-1308. IEEE. DOI= 10.1109\/ICIRCA.2018.8597266"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-33585-4_40"},{"key":"e_1_3_2_1_13_1","first-page":"42","volume-title":"Neurocomputing, (Jul 2018","author":"Wu Pengcheng","year":"2018","unstructured":"Xudong. Sun, Pengcheng Wu , and Steven CH Hoi . 2018 . Face detection using deep learning: An improved faster RCNN approach. 2018. Face detection using deep learning: An improved faster RCNN approach . Neurocomputing, (Jul 2018 ), 299, pp. 42 - 50 . DOI= https:\/\/doi.org\/10.1016\/j.neucom.2018.03.030 10.1016\/j.neucom.2018.03.030 Xudong. Sun, Pengcheng Wu, and Steven CH Hoi. 2018. Face detection using deep learning: An improved faster RCNN approach. 2018. Face detection using deep learning: An improved faster RCNN approach. Neurocomputing, (Jul 2018), 299, pp.42-50. DOI= https:\/\/doi.org\/10.1016\/j.neucom.2018.03.030"},{"key":"e_1_3_2_1_14_1","volume-title":"Proceedings of the IEEE conference on computer vision and pattern recognition. (pp. 5686-5695)","author":"Liu Mason","year":"2018","unstructured":"Mason Liu , and Menglong Zhu . 2018 . Mobile video object detection with temporally-aware feature maps . In Proceedings of the IEEE conference on computer vision and pattern recognition. (pp. 5686-5695) . DOI= 10.1109\/CVPR.2018.00596 Mason Liu, and Menglong Zhu. 2018. Mobile video object detection with temporally-aware feature maps. In Proceedings of the IEEE conference on computer vision and pattern recognition. (pp. 5686-5695). DOI= 10.1109\/CVPR.2018.00596"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/IWAIT.2018.8369633"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-15702-8_33"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1186\/s40537-021-00434-w"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11265-016-1114-9"},{"key":"e_1_3_2_1_19_1","volume-title":"Mobile Information Systems","author":"Wang Wei","year":"2020","unstructured":"Wei Wang , Yutao Li , Ting Zou , Xin Wang , Jieyu You , and Yanhong Luo . 2020 . A novel image classification approach via dense-MobileNet models . Mobile Information Systems , Jan 2020. DOI= https:\/\/doi.org\/10.1155\/2020\/7602384 10.1155\/2020 Wei Wang, Yutao Li, Ting Zou, Xin Wang, Jieyu You, and Yanhong Luo. 2020. A novel image classification approach via dense-MobileNet models. Mobile Information Systems, Jan 2020. DOI= https:\/\/doi.org\/10.1155\/2020\/7602384"},{"key":"e_1_3_2_1_20_1","first-page":"65","volume-title":"Senthil Kumar Thangavel, and Latha Parameswaran","author":"Kumar Sanjay","year":"2021","unstructured":"Sanjay Kumar , K. K. R. , Goutham Subramani , Senthil Kumar Thangavel, and Latha Parameswaran . 2021 . A mobile-based framework for detecting objects using ssd-mobilenet in indoor environment. In Intelligence in Big Data Technologies\u2014Beyond the Hype : Proceedings of ICBDCC 2019 (pp. 65 - 76 ). Springer . DOI= https:\/\/doi.org\/10.1007\/978-981-15-5285-4_6 10.1007\/978-981-15-5285-4_6 Sanjay Kumar, K. K. R., Goutham Subramani, Senthil Kumar Thangavel, and Latha Parameswaran. 2021. A mobile-based framework for detecting objects using ssd-mobilenet in indoor environment. In Intelligence in Big Data Technologies\u2014Beyond the Hype: Proceedings of ICBDCC 2019 (pp. 65-76). Springer. DOI= https:\/\/doi.org\/10.1007\/978-981-15-5285-4_6"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.3390\/electronics11172782"}],"event":{"name":"ASIA CCS '23: ACM Asia Conference on Computer and Communications Security","location":"Melbourne VIC Australia","acronym":"ASIA CCS '23","sponsor":["SIGSAC ACM Special Interest Group on Security, Audit, and Control"]},"container-title":["Proceedings of the 5th ACM International Symposium on Blockchain and Secure Critical Infrastructure"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3594556.3594619","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3594556.3594619","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T18:09:07Z","timestamp":1750183747000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3594556.3594619"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,10]]},"references-count":22,"alternative-id":["10.1145\/3594556.3594619","10.1145\/3594556"],"URL":"https:\/\/doi.org\/10.1145\/3594556.3594619","relation":{},"subject":[],"published":{"date-parts":[[2023,7,10]]},"assertion":[{"value":"2023-09-12","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}