{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T01:04:18Z","timestamp":1784163858211,"version":"3.55.0"},"publisher-location":"New York, NY, USA","reference-count":71,"publisher":"ACM","license":[{"start":{"date-parts":[[2026,2,9]],"date-time":"2026-02-09T00:00:00Z","timestamp":1770595200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,2,9]]},"DOI":"10.1145\/3793811.3793820","type":"proceedings-article","created":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T12:23:01Z","timestamp":1783081381000},"page":"42-51","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["A Comparative Analysis of Deep Learning Models for Deployment on an Australian Bushfire Detection Satellite"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5998-222X","authenticated-orcid":false,"suffix":"Prof","given":"Richard O.","family":"Sinnott","sequence":"first","affiliation":[{"name":"School of Computing and Information Systems, University of Melbourne, Melbourne, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-1863-0874","authenticated-orcid":false,"given":"Travis","family":"Davies","sequence":"additional","affiliation":[{"name":"School of Computing and Information Systems, University of Melbourne, Melbourne, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,7,3]]},"reference":[{"key":"e_1_3_3_1_2_2","doi-asserted-by":"publisher","unstructured":"Emanuele Alcaras Domenica Costantino Francesca Guastaferro Claudio Parente and Massimiliano Pepe. 2022. Normalized Burn Ratio Plus (NBR+): A New Index for Sentinel-2 Imagery. Remote Sensing 14 7 (2022). 10.3390\/rs14071727","DOI":"10.3390\/rs14071727"},{"key":"e_1_3_3_1_3_2","doi-asserted-by":"publisher","unstructured":"Basim Azam Muhammad\u00a0Jaleed Khan Farrukh\u00a0Aziz Bhatti Abdur Rahman\u00a0M. Maud Syed\u00a0Fawad Hussain Ali\u00a0Javed Hashmi and Khurram Khurshid. 2022. Aircraft detection in satellite imagery using deep learning-based object detectors. Microprocessors and Microsystems 94 (2022) 104630. 10.1016\/j.micpro.2022.104630","DOI":"10.1016\/j.micpro.2022.104630"},{"key":"e_1_3_3_1_4_2","doi-asserted-by":"publisher","unstructured":"A.\u00a0K. Brand and A. Manandhar. 2021. SEMANTIC SEGMENTATION OF BURNED AREAS IN SATELLITE IMAGES USING A U-NET-BASED CONVOLUTIONAL NEURAL NETWORK. The International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences XLIII-B3-2021 (2021) 47\u201353. 10.5194\/isprs-archives-XLIII-B3-2021-47-2021","DOI":"10.5194\/isprs-archives-XLIII-B3-2021-47-2021"},{"key":"e_1_3_3_1_5_2","unstructured":"Tom\u00a0B. Brown Benjamin Mann Nick Ryder Melanie Subbiah Jared Kaplan Prafulla Dhariwal Arvind Neelakantan Pranav Shyam Girish Sastry Amanda Askell Sandhini Agarwal Ariel Herbert-Voss Gretchen Krueger Tom Henighan Rewon Child Aditya Ramesh Daniel\u00a0M. Ziegler Jeff Wu Clemens Winter Christopher Hesse Mark Chen Eric Sigler Mateusz Litwin Scott Gray Benjamin Chess Jack Clark Christopher Berner Sam McCandlish Alec Radford Ilya Sutskever and Dario Amodei. 2020. Language Models are Few-Shot Learners. ArXiv abs\/2005.14165 (2020). https:\/\/api.semanticscholar.org\/CorpusID:218971783"},{"key":"e_1_3_3_1_6_2","unstructured":"Ben Butler. 2020. Economic Impact of Australia\u2019s Bushfires Set to Exceed $4.4 Bn Cost of Black Saturday. The Guardian (2020). https:\/\/www.theguardian.com\/australianews\/2020\/jan\/08\/economic-impact-of-\/ australias-bushfires-set-to-exceed-44bn-cost-of-black-saturday"},{"key":"e_1_3_3_1_7_2","doi-asserted-by":"publisher","unstructured":"Junyi Chai Hao Zeng Anming Li and Eric\u00a0W.T. Ngai. 2021. Deep learning in computer vision: A critical review of emerging techniques and application scenarios. Machine Learning with Applications 6 (2021) 100134. 10.1016\/j.mlwa.2021.100134","DOI":"10.1016\/j.mlwa.2021.100134"},{"key":"e_1_3_3_1_8_2","unstructured":"Liang-Chieh Chen George Papandreou Florian Schroff and Hartwig Adam. 2017. Rethinking Atrous Convolution for Semantic Image Segmentation. ArXiv abs\/1706.05587 (2017). https:\/\/api.semanticscholar.org\/CorpusID:22655199"},{"key":"e_1_3_3_1_9_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00290"},{"key":"e_1_3_3_1_10_2","doi-asserted-by":"publisher","unstructured":"D. Comaniciu and P. Meer. 2002. Mean shift: a robust approach toward feature space analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence 24 5 (2002) 603\u2013619. 10.1109\/34.1000236","DOI":"10.1109\/34.1000236"},{"key":"e_1_3_3_1_11_2","unstructured":"Copernicus. [n. d.]. Sentinel-2 Input Data Documentation. Available here: https:\/\/s2.pages.eopf.copernicus.eu\/pdfs-adfs\/MSI\/index.html#spectral-resolution. Accessed on 2024-04-06."},{"key":"e_1_3_3_1_12_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW63382.2024.00672"},{"key":"e_1_3_3_1_13_2","volume-title":"North American Chapter of the Association for Computational Linguistics","author":"Devlin Jacob","year":"2019","unstructured":"Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In North American Chapter of the Association for Computational Linguistics. https:\/\/api.semanticscholar.org\/CorpusID:52967399"},{"key":"e_1_3_3_1_14_2","doi-asserted-by":"publisher","unstructured":"Wei Fang Yuxiang Fu and Victor\u00a0S. Sheng. 2024. Dual Backbone Interaction Network for Burned Area Segmentation in Optical Remote Sensing Images. IEEE Geoscience and Remote Sensing Letters 21 (2024) 1\u20135. 10.1109\/LGRS.2024.3369619","DOI":"10.1109\/LGRS.2024.3369619"},{"key":"e_1_3_3_1_15_2","doi-asserted-by":"crossref","unstructured":"Pedro\u00a0F. Felzenszwalb and Daniel\u00a0P. Huttenlocher. 2004. Efficient Graph-Based Image Segmentation. International Journal of Computer Vision 59 (2004) 167\u2013181. https:\/\/api.semanticscholar.org\/CorpusID:207663697","DOI":"10.1023\/B:VISI.0000022288.19776.77"},{"key":"e_1_3_3_1_16_2","doi-asserted-by":"publisher","unstructured":"Alexander\u00a0I. Filkov Tuan Ngo Stuart Matthews Simeon Telfer and Trent\u00a0D. Penman. 2020. Impact of Australia\u2019s catastrophic 2019\/20 bushfire season on communities and environment. Retrospective analysis and current trends. Journal of Safety Science and Resilience 1 1 (2020) 44\u201356. 10.1016\/j.jnlssr.2020.06.009","DOI":"10.1016\/j.jnlssr.2020.06.009"},{"key":"e_1_3_3_1_17_2","doi-asserted-by":"publisher","unstructured":"Matt Finer Sidney Novoa Mikaela\u00a0J. Weisse Rachael Petersen Joseph Mascaro Tamia Souto Forest Stearns and Ra\u00fal\u00a0Garc\u00eda Martinez. 2018. Combating deforestation: From satellite to intervention. Science 360 6395 (2018) 1303\u20131305. 10.1126\/science.aat1203 arXiv:https:\/\/www.science.org\/doi\/pdf\/10.1126\/science.aat1203","DOI":"10.1126\/science.aat1203"},{"key":"e_1_3_3_1_18_2","unstructured":"ANU\u00a0Institute for Space. 2021. OzFuel Pre-Phase A Study: Australian Forest Fuel Monitoring From Space. ANU Institute for Space (2021)."},{"key":"e_1_3_3_1_19_2","doi-asserted-by":"publisher","unstructured":"M.J.\u00a0L\u00f3pez Garc\u00eda and V. Caselles. 1991. Mapping burns and natural reforestation using thematic Mapper data. Geocarto International 6 1 (1991) 31\u201337. 10.1080\/10106049109354290 arXiv:10.1080\/10106049109354290","DOI":"10.1080\/10106049109354290"},{"key":"e_1_3_3_1_20_2","doi-asserted-by":"crossref","unstructured":"Andreas Geiger Philip Lenz Christoph Stiller and Raquel Urtasun. 2013. Vision meets robotics: The kitti dataset. The International Journal of Robotics Research 32 11 (2013) 1231\u20131237.","DOI":"10.1177\/0278364913491297"},{"key":"e_1_3_3_1_21_2","unstructured":"Australian Government. [n. d.]. Sentinel Australasia Regional Acess Platform. Available here: https:\/\/copernicus.nci.org.au\/sara.client\/#\/home. Accessed 2024-04-08."},{"key":"e_1_3_3_1_22_2","unstructured":"Australian Government. 2022. The Now Frontier: Developing Australia\u2019s Space Industry. Australian Government (2022)."},{"key":"e_1_3_3_1_23_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01204"},{"key":"e_1_3_3_1_24_2","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops","author":"Gupta Ritwik","year":"2019","unstructured":"Ritwik Gupta, Bryce Goodman, Nirav Patel, Ricky Hosfelt, Sandra Sajeev, Eric Heim, Jigar Doshi, Keane Lucas, Howie Choset, and Matthew Gaston. 2019. Creating xBD: A Dataset for Assessing Building Damage from Satellite Imagery. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops."},{"key":"e_1_3_3_1_25_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.322"},{"key":"e_1_3_3_1_26_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_3_3_1_27_2","volume-title":"NIPS Deep Learning and Representation Learning Workshop","author":"Hinton Geoffrey","year":"2015","unstructured":"Geoffrey Hinton, Oriol Vinyals, and Jeffrey Dean. 2015. Distilling the Knowledge in a Neural Network. In NIPS Deep Learning and Representation Learning Workshop. http:\/\/arxiv.org\/abs\/1503.02531"},{"key":"e_1_3_3_1_28_2","unstructured":"NVIDIA\u00a0AI IOT. 2023. NanoSAM. https:\/\/github.com\/NVIDIA-AI-IOT\/nanosam\/tree\/main."},{"key":"e_1_3_3_1_29_2","doi-asserted-by":"crossref","unstructured":"Ali I\u015f\u0131n Cem Direko\u011flu and Melike \u015eah. 2016. Review of MRI-based brain tumor image segmentation using deep learning methods. Procedia Computer Science 102 (2016) 317\u2013324.","DOI":"10.1016\/j.procs.2016.09.407"},{"key":"e_1_3_3_1_30_2","doi-asserted-by":"crossref","unstructured":"Jacob\u00a0H\u00f8xbroe Jeppesen Rune\u00a0Hylsberg Jacobsen Fadil Inceoglu and Thomas\u00a0Skj\u00f8deberg Toftegaard. 2019. A cloud detection algorithm for satellite imagery based on deep learning. Remote sensing of environment 229 (2019) 247\u2013259.","DOI":"10.1016\/j.rse.2019.03.039"},{"key":"e_1_3_3_1_31_2","doi-asserted-by":"publisher","unstructured":"Wazir\u00a0Zada Khan Ejaz Ahmed Saqib Hakak Ibrar Yaqoob and Arif Ahmed. 2019. Edge computing: A survey. Future Generation Computer Systems 97 (2019) 219\u2013235. 10.1016\/j.future.2019.02.050","DOI":"10.1016\/j.future.2019.02.050"},{"key":"e_1_3_3_1_32_2","doi-asserted-by":"crossref","unstructured":"Alexander Kirillov Eric Mintun Nikhila Ravi Hanzi Mao Chloe Rolland Laura Gustafson Tete Xiao Spencer Whitehead Alexander\u00a0C. Berg Wan-Yen Lo Piotr Doll\u00e1r and Ross Girshick. 2023. Segment Anything. arXiv:https:\/\/arXiv.org\/abs\/2304.02643 (2023).","DOI":"10.1109\/ICCV51070.2023.00371"},{"key":"e_1_3_3_1_33_2","unstructured":"Alexander Kolesnikov Alexey Dosovitskiy Dirk Weissenborn Georg Heigold Jakob Uszkoreit Lucas Beyer Matthias Minderer Mostafa Dehghani Neil Houlsby Sylvain Gelly Thomas Unterthiner and Xiaohua Zhai. 2021. An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale."},{"key":"e_1_3_3_1_34_2","doi-asserted-by":"publisher","unstructured":"Alex Krizhevsky Ilya Sutskever and Geoffrey\u00a0E. Hinton. 2017. ImageNet classification with deep convolutional neural networks. Commun. ACM 60 6 (may 2017) 84\u201390. 10.1145\/3065386","DOI":"10.1145\/3065386"},{"key":"e_1_3_3_1_35_2","unstructured":"Stephen Kuper. 2020. ANU scientists to use eyes in space to spot bushfire danger zones. Space Connect (2020). https:\/\/www.spaceconnectonline.com.au\/industry\/4214-anu-scientists-to-use-eyes-in-space-to-spot-bushfire-danger-zones"},{"key":"e_1_3_3_1_36_2","doi-asserted-by":"crossref","unstructured":"Isabella\u00a0K Lee John\u00a0C Trinder and Arcot Sowmya. 2020. Application of u-net convolutional neural network to bushfire monitoring in Australia with sentinel-1\/-2 data. The International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences 43 (2020) 573\u2013578.","DOI":"10.5194\/isprs-archives-XLIII-B1-2020-573-2020"},{"key":"e_1_3_3_1_37_2","doi-asserted-by":"publisher","unstructured":"Sha Lu Eriita Jones Liang Zhao Yu Sun Kai Qin Jixue Liu Jiuyong Li Prabath Abeysekara Norman Mueller Simon Oliver Jim O\u2019Hehir and Stefan Peters. 2024. Onboard AI for Fire Smoke Detection Using Hyperspectral Imagery: An Emulation for the Upcoming Kanyini Hyperscout-2 Mission. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 17 (2024) 9629\u20139640. 10.1109\/JSTARS.2024.3394574","DOI":"10.1109\/JSTARS.2024.3394574"},{"key":"e_1_3_3_1_38_2","doi-asserted-by":"crossref","unstructured":"Jun Ma Jack\u00a0CP Cheng Feifeng Jiang Vincent\u00a0JL Gan Mingzhu Wang and Chong Zhai. 2020. Real-time detection of wildfire risk caused by powerline vegetation faults using advanced machine learning techniques. Advanced Engineering Informatics 44 (2020) 101070.","DOI":"10.1016\/j.aei.2020.101070"},{"key":"e_1_3_3_1_39_2","volume-title":"ICLR","author":"Mehta Sachin","year":"2022","unstructured":"Sachin Mehta and Mohammad Rastegari. 2022. MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer. In ICLR. https:\/\/arxiv.org\/abs\/2110.02178"},{"key":"e_1_3_3_1_40_2","doi-asserted-by":"publisher","unstructured":"Sachin Mehta Mohammad Rastegari Linda Shapiro and Hannaneh Hajishirzi. 2019. ESPNetv2: A Light-Weight Power Efficient and General Purpose Convolutional Neural Network. 9182\u20139192. 10.1109\/CVPR.2019.00941","DOI":"10.1109\/CVPR.2019.00941"},{"key":"e_1_3_3_1_41_2","doi-asserted-by":"publisher","unstructured":"Shervin Minaee Yuri Boykov Fatih Porikli Antonio Plaza Nasser Kehtarnavaz and Demetri Terzopoulos. 2022. Image Segmentation Using Deep Learning: A Survey. IEEE Transactions on Pattern Analysis and Machine Intelligence 44 7 (2022) 3523\u20133542. 10.1109\/TPAMI.2021.3059968","DOI":"10.1109\/TPAMI.2021.3059968"},{"key":"e_1_3_3_1_42_2","doi-asserted-by":"publisher","unstructured":"Yue Ming Xuyang Meng Chunxiao Fan and Hui Yu. 2021. Deep learning for monocular depth estimation: A review. Neurocomputing 438 (2021) 14\u201333. 10.1016\/j.neucom.2020.12.089","DOI":"10.1016\/j.neucom.2020.12.089"},{"key":"e_1_3_3_1_43_2","doi-asserted-by":"publisher","unstructured":"Thanh\u00a0Tam Nguyen Thanh\u00a0Dat Hoang Minh\u00a0Tam Pham Tuyet\u00a0Trinh Vu Thanh\u00a0Hung Nguyen Quyet-Thang Huynh and Jun Jo. 2020. Monitoring agriculture areas with satellite images and deep learning. Applied Soft Computing 95 (2020) 106565. 10.1016\/j.asoc.2020.106565","DOI":"10.1016\/j.asoc.2020.106565"},{"key":"e_1_3_3_1_44_2","unstructured":"Australian\u00a0Bureau of Statistics. 2022-23. Regional population. Available here: https:\/\/www.abs.gov.au\/statistics\/people\/population\/regional-population\/2022-23. Accessed 2024-08-04."},{"key":"e_1_3_3_1_45_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-12931-6_12"},{"key":"e_1_3_3_1_46_2","unstructured":"Maxime Oquab Timoth\u00e9e Darcet Th\u00e9o Moutakanni Huy Vo Marc Szafraniec Vasil Khalidov Pierre Fernandez Daniel Haziza Francisco Massa Alaaeldin El-Nouby Mahmoud Assran Nicolas Ballas Wojciech Galuba Russell Howes Po-Yao Huang Shang-Wen Li Ishan Misra Michael Rabbat Vasu Sharma Gabriel Synnaeve Hu Xu Herv\u00e9 Jegou Julien Mairal Patrick Labatut Armand Joulin and Piotr Bojanowski. 2024. DINOv2: Learning Robust Visual Features without Supervision. arxiv:https:\/\/arXiv.org\/abs\/2304.07193\u00a0[cs.CV]"},{"key":"e_1_3_3_1_47_2","doi-asserted-by":"publisher","unstructured":"Nobuyuki Otsu. 1979. A Threshold Selection Method from Gray-Level Histograms. IEEE Transactions on Systems Man and Cybernetics 9 1 (1979) 62\u201366. 10.1109\/TSMC.1979.4310076","DOI":"10.1109\/TSMC.1979.4310076"},{"key":"e_1_3_3_1_48_2","unstructured":"Juncai Peng Yi Liu Shiyu Tang Yuying Hao Lutao Chu Guowei Chen Zewu Wu Zeyu Chen Zhiliang Yu Yuning Du Qingqing Dang Baohua Lai Qiwen Liu Xiaoguang Hu Dianhai Yu and Yanjun Ma. 2022. PP-LiteSeg: A Superior Real-Time Semantic Segmentation Model. ArXiv abs\/2204.02681 (2022). https:\/\/api.semanticscholar.org\/CorpusID:247996837"},{"key":"e_1_3_3_1_49_2","series-title":"Proceedings of Machine Learning Research","first-page":"1135","volume-title":"Proceedings of the 15th Asian Conference on Machine Learning","volume":"222","author":"Rad Ryan","year":"2024","unstructured":"Ryan Rad. 2024. Remote Wildfire Detection using Multispectral Satellite Imagery and Vision Transformers. In Proceedings of the 15th Asian Conference on Machine Learning(Proceedings of Machine Learning Research, Vol.\u00a0222), Berrin Yan\u0131ko\u011flu and Wray Buntine (Eds.). PMLR, 1135\u20131150. https:\/\/proceedings.mlr.press\/v222\/rad24a.html"},{"key":"e_1_3_3_1_50_2","unstructured":"Graham Readfearn. 2020. Philanthropic foundation dreams of extinguishing all bushfires \u2019within an hour\u2019 with high-tech help. The Guardian (2020). https:\/\/www.theguardian.com\/australia-news\/2020\/sep\/15\/philanthropic-foundation-dreams-of-extinguishing-all-bushfires-\/within-an-hour-with-high-tech-help"},{"key":"e_1_3_3_1_51_2","unstructured":"National Recovery and Resilience Agency. 2020. 2020 National Operational Bushfire Boundaries dataset. Available here: https:\/\/data.gov.au\/data\/dataset\/2020-operational-bushfire-boundaries. Accessed 2024-03-08."},{"key":"e_1_3_3_1_52_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"e_1_3_3_1_53_2","doi-asserted-by":"publisher","unstructured":"Carsten Rother Vladimir Kolmogorov and Andrew Blake. 2004. GrabCut: Interactive Foreground Extraction Using Iterated Graph Cuts. ACM Trans. Graph. 23 (08 2004) 309\u2013314. 10.1145\/1186562.1015720","DOI":"10.1145\/1186562.1015720"},{"key":"e_1_3_3_1_54_2","doi-asserted-by":"crossref","unstructured":"Vivien Sainte Fare\u00a0Garnot and Loic Landrieu. 2021. Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networks. ICCV (2021).","DOI":"10.1109\/ICCV48922.2021.00483"},{"key":"e_1_3_3_1_55_2","doi-asserted-by":"crossref","unstructured":"Seyd\u00a0Teymoor Seydi Vahideh Saeidi Bahareh Kalantar Naonori Ueda and Alfian\u00a0Abdul Halin. 2022. Fire-Net: A deep learning framework for active forest fire detection. Journal of Sensors 2022 (2022) 1\u201314.","DOI":"10.1155\/2022\/8044390"},{"key":"e_1_3_3_1_56_2","doi-asserted-by":"publisher","unstructured":"Evan Shelhamer Jonathan Long and Trevor Darrell. 2017. Fully Convolutional Networks for Semantic Segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence 39 4 (2017) 640\u2013651. 10.1109\/TPAMI.2016.2572683","DOI":"10.1109\/TPAMI.2016.2572683"},{"key":"e_1_3_3_1_57_2","doi-asserted-by":"publisher","unstructured":"Jianbo Shi and J. Malik. 2000. Normalized cuts and image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence 22 8 (2000) 888\u2013905. 10.1109\/34.868688","DOI":"10.1109\/34.868688"},{"key":"e_1_3_3_1_58_2","unstructured":"Karen Simonyan and Andrew Zisserman. 2014. Very Deep Convolutional Networks for Large-Scale Image Recognition. arXiv 1409.1556 (09 2014)."},{"key":"e_1_3_3_1_59_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"e_1_3_3_1_60_2","doi-asserted-by":"publisher","DOI":"10.5555\/1941882"},{"key":"e_1_3_3_1_61_2","doi-asserted-by":"publisher","unstructured":"Kathiravan Thangavel Dario Spiller Roberto Sabatini Stefania Amici Sarathchandrakumar\u00a0Thottuchirayil Sasidharan Haytham Fayek and Pier Marzocca. 2023. Autonomous Satellite Wildfire Detection Using Hyperspectral Imagery and Neural Networks: A Case Study on Australian Wildfire. Remote Sensing 15 3 (2023). 10.3390\/rs15030720","DOI":"10.3390\/rs15030720"},{"key":"e_1_3_3_1_62_2","doi-asserted-by":"publisher","unstructured":"Kathiravan Thangavel Dario Spiller Roberto Sabatini Pier Marzocca and Marco Esposito. 2023. Near Real-Time Wildfire Management Using Distributed Satellite System. IEEE Geoscience and Remote Sensing Letters 20 (2023) 1\u20135. 10.1109\/LGRS.2022.3229173","DOI":"10.1109\/LGRS.2022.3229173"},{"key":"e_1_3_3_1_63_2","unstructured":"Adam Thorn. [n. d.]. Bushfire-detecting Kanyini passes pre-launch tests. Space Connect ([n. d.]). https:\/\/www.spaceconnectonline.com.au\/satellites\/6159-bushfire-detecting-kanyini-passes-pre-launch-tests"},{"key":"e_1_3_3_1_64_2","unstructured":"Adam Thorn. 2024. Australia primed to be leader in bushfire detection. Space Connect (2024). https:\/\/www.spaceconnectonline.com.au\/satellites\/6119-australia-primed-to-be-leader-in-bushfire-detection"},{"key":"e_1_3_3_1_65_2","unstructured":"Jamie Tolan Camille Couprie and Tracy Johns. 2023. Every tree counts: Large-scale mapping of canopy height at the resolution of individual trees. Available here: https:\/\/research.facebook.com\/blog\/2023\/4\/every-tree-counts-large-scale-mapping-of-canopy-height-at-the-resolution-of-individual-trees. (2023). Accessed on 2024-05-13."},{"key":"e_1_3_3_1_66_2","unstructured":"Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan\u00a0N. Gomez Lukasz Kaiser and Illia Polosukhin. 2017. Attention is All You Need. https:\/\/arxiv.org\/pdf\/1706.03762.pdf"},{"key":"e_1_3_3_1_67_2","first-page":"30392","volume-title":"Advances in Neural Information Processing Systems","author":"Xiao Tete","year":"2021","unstructured":"Tete Xiao, Mannat Singh, Eric Mintun, Trevor Darrell, Piotr Dollar, and Ross Girshick. 2021. Early Convolutions Help Transformers See Better. In Advances in Neural Information Processing Systems , M.\u00a0Ranzato, A.\u00a0Beygelzimer, Y.\u00a0Dauphin, P.S. Liang, and J.\u00a0Wortman Vaughan (Eds.), Vol.\u00a034. Curran Associates, Inc., 30392\u201330400. https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2021\/file\/ff1418e8cc993fe8abcfe3ce2003e5c5-Paper.pdf"},{"key":"e_1_3_3_1_68_2","volume-title":"Neural Information Processing Systems (NeurIPS)","author":"Xie Enze","year":"2021","unstructured":"Enze Xie, Wenhai Wang, Zhiding Yu, Anima Anandkumar, Jose\u00a0M Alvarez, and Ping Luo. 2021. SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers. In Neural Information Processing Systems (NeurIPS)."},{"key":"e_1_3_3_1_69_2","doi-asserted-by":"crossref","unstructured":"Changqian Yu Changxin Gao Jingbo Wang Gang Yu Chunhua Shen and Nong Sang. 2020. BiSeNet V2: Bilateral Network with Guided Aggregation for Real-Time Semantic Segmentation. International Journal of Computer Vision 129 (2020) 3051 \u2013 3068. https:\/\/api.semanticscholar.org\/CorpusID:214802217","DOI":"10.1007\/s11263-021-01515-2"},{"key":"e_1_3_3_1_70_2","unstructured":"Syed\u00a0Waqas Zamir Aditya Arora Akshita Gupta Salman\u00a0Hameed Khan Guolei Sun Fahad\u00a0Shahbaz Khan Fan Zhu Ling Shao Guisong Xia and Xiang Bai. 2019. iSAID: A Large-scale Dataset for Instance Segmentation in Aerial Images. ArXiv abs\/1905.12886 (2019). https:\/\/api.semanticscholar.org\/CorpusID:170079084"},{"key":"e_1_3_3_1_71_2","unstructured":"Chaoning Zhang Dongshen Han Yu Qiao Jung\u00a0Uk Kim Sung-Ho Bae Seungkyu Lee and Choong\u00a0Seon Hong. 2023. Faster Segment Anything: Towards Lightweight SAM for Mobile Applications. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2306.14289 (2023)."},{"key":"e_1_3_3_1_72_2","doi-asserted-by":"publisher","unstructured":"Fuzhen Zhuang Zhiyuan Qi Keyu Duan Dongbo Xi Yongchun Zhu Hengshu Zhu Hui Xiong and Qing He. 2021. A Comprehensive Survey on Transfer Learning. Proc. IEEE 109 1 (2021) 43\u201376. 10.1109\/JPROC.2020.3004555","DOI":"10.1109\/JPROC.2020.3004555"}],"event":{"name":"ACSW 2026: 2026 Australasian Computer Science Week","location":"Melbourne Australia","acronym":"ACSW 2026"},"container-title":["Proceedings of the 2026 Australasian Computer Science Week"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3793811.3793820","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T01:01:42Z","timestamp":1784163702000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3793811.3793820"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2,9]]},"references-count":71,"alternative-id":["10.1145\/3793811.3793820","10.1145\/3793811"],"URL":"https:\/\/doi.org\/10.1145\/3793811.3793820","relation":{},"subject":[],"published":{"date-parts":[[2026,2,9]]},"assertion":[{"value":"2026-07-03","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}