{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T10:53:05Z","timestamp":1767178385158,"version":"3.48.0"},"publisher-location":"New York, NY, USA","reference-count":12,"publisher":"ACM","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,1,6]]},"DOI":"10.1145\/3737611.3776612","type":"proceedings-article","created":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T10:35:20Z","timestamp":1767177320000},"page":"66-71","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Scene-Aware Low-Light Image Enhancement using Multi-scale Image Restoration Network using Diverse Optimizers for Vision-Based Intelligent Transportation System"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-5770-3785","authenticated-orcid":false,"given":"Hrusikesh","family":"Nishank","sequence":"first","affiliation":[{"name":"Computer Science and Engineering, Indian Institute of Information Technology and Management (IIITM), Gwalior, Madhya Pradesh, India"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-2342-1630","authenticated-orcid":false,"given":"Siddhant","family":"Kumar","sequence":"additional","affiliation":[{"name":"Computer Science and Engineering, Indian Institute of Information Technology and Management (IIITM), Gwalior, Madhya Pradesh, India"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-5396-1882","authenticated-orcid":false,"given":"Adarsh Singh","family":"Jadon","sequence":"additional","affiliation":[{"name":"Computer Science and Engineering, Indian Institute of Information Technology and Management (IIITM), Gwalior, Madhya Pradesh, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4579-1419","authenticated-orcid":false,"given":"Chittaranjan","family":"Swain","sequence":"additional","affiliation":[{"name":"Computer Science and Engineering, Indian Institute of Information Technology and Management (IIITM), Gwalior, Madhya Pradesh, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7411-5113","authenticated-orcid":false,"given":"Vivek","family":"Tiwari","sequence":"additional","affiliation":[{"name":"Computer Science and Engineering, Indian Institute of Information Technology and Management (IIITM), Gwalior, Madhya Pradesh, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0160-4215","authenticated-orcid":false,"given":"Deepak Kumar","family":"Dewangan","sequence":"additional","affiliation":[{"name":"Computer Science and Engineering, Indian Institute of Information Technology and Management (IIITM), Gwalior, Madhya Pradesh, India"}]}],"member":"320","published-online":{"date-parts":[[2026,1,4]]},"reference":[{"key":"e_1_3_3_1_2_2","volume-title":"Proceedings of the Twenty-Fourth IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","author":"Bychkovsky Vladimir","year":"2011","unstructured":"Vladimir Bychkovsky, Sylvain Paris, Eric Chan, and Fr\u00e9do Durand. 2011. Learning Photographic Global Tonal Adjustment with a Database of Input\/Output Image Pairs. In Proceedings of the Twenty-Fourth IEEE Conference on Computer Vision and Pattern Recognition (CVPR)."},{"key":"e_1_3_3_1_3_2","doi-asserted-by":"crossref","unstructured":"Deepak\u00a0Kumar Dewangan and Satya\u00a0Prakash Sahu. 2020. Driving behavior analysis of intelligent vehicle system for lane detection using vision-sensor. IEEE Sensors Journal 21 5 (2020) 6367\u20136375.","DOI":"10.1109\/JSEN.2020.3037340"},{"key":"e_1_3_3_1_4_2","unstructured":"Diederik\u00a0P. Kingma and Jimmy Ba. 2014. Adam: A Method for Stochastic Optimization. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/1412.6980 (2014). https:\/\/arxiv.org\/abs\/1412.6980"},{"key":"e_1_3_3_1_5_2","unstructured":"Liu Liu Haoming Jian Pengcheng He and Weizhu Chen. 2019. On the Variance of the Adaptive Learning Rate and Beyond. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/1908.03265 (2019). https:\/\/arxiv.org\/abs\/1908.03265"},{"key":"e_1_3_3_1_6_2","doi-asserted-by":"publisher","unstructured":"Kin\u00a0Gwn Lore Adedotun Akintayo and Soumik Sarkar. 2017. LLNet: A Deep Autoencoder Approach to Natural Low-Light Image Enhancement. Pattern Recognition 61 (2017) 650\u2013662. 10.1016\/j.patcog.2016.06.008","DOI":"10.1016\/j.patcog.2016.06.008"},{"key":"e_1_3_3_1_7_2","unstructured":"Ilya Loshchilov and Frank Hutter. 2017. Decoupled Weight Decay Regularization. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/1711.05101 (2017). https:\/\/arxiv.org\/abs\/1711.05101"},{"key":"e_1_3_3_1_8_2","doi-asserted-by":"publisher","unstructured":"Zhou Wang Alan\u00a0C. Bovik Hamid\u00a0R. Sheikh and Eero\u00a0P. Simoncelli. 2004. Image Quality Assessment: From Error Visibility to Structural Similarity. IEEE Transactions on Image Processing 13 4 (2004) 600\u2013612. 10.1109\/TIP.2003.819861","DOI":"10.1109\/TIP.2003.819861"},{"key":"e_1_3_3_1_9_2","volume-title":"Proceedings of the British Machine Vision Conference (BMVC)","author":"Wei Chen","year":"2018","unstructured":"Chen Wei, Wenjing Wang, Wenhan Yang, and Jiaying Liu. 2018. Deep Retinex Decomposition for Low-Light Enhancement. In Proceedings of the British Machine Vision Conference (BMVC)."},{"key":"e_1_3_3_1_10_2","unstructured":"Less Wright and Nestor Demeure. 2021. Ranger21: A Synergistic Deep Learning Optimizer. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2106.13731 (2021). https:\/\/arxiv.org\/abs\/2106.13731"},{"key":"e_1_3_3_1_11_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58595-2_30"},{"key":"e_1_3_3_1_12_2","doi-asserted-by":"publisher","unstructured":"Syed\u00a0Waqas Zamir Aditya Arora Salman\u00a0H. Khan Munawar Hayat Fahad\u00a0Shahbaz Khan Ming-Hsuan Yang and Ling Shao. 2023. Learning Enriched Features for Fast Image Restoration and Enhancement. IEEE Transactions on Pattern Analysis and Machine Intelligence 45 2 (2023) 1934\u20131948. 10.1109\/TPAMI.2022.3167175","DOI":"10.1109\/TPAMI.2022.3167175"},{"key":"e_1_3_3_1_13_2","first-page":"18795","volume-title":"Advances in Neural Information Processing Systems (NeurIPS)","author":"Zhuang Juntang","year":"2020","unstructured":"Juntang Zhuang, Tommy Tang, Yifan Ding, Sekhar Tatikonda, Nicha Dvornek, Xenophon Papademetris, and James\u00a0S. Duncan. 2020. AdaBelief Optimizer: Adapting Stepsizes by the Belief in Observed Gradients. In Advances in Neural Information Processing Systems (NeurIPS) , Vol.\u00a033. 18795\u201318806."}],"event":{"name":"ICDCN 2026: 27th International Conference on Distributed Computing and Networking","acronym":"ICDCN Companion 2026","location":"Nara Japan"},"container-title":["Companion Proceedings of the 27th International Conference on Distributed Computing and Networking"],"original-title":[],"deposited":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T10:49:02Z","timestamp":1767178142000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3737611.3776612"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,4]]},"references-count":12,"alternative-id":["10.1145\/3737611.3776612","10.1145\/3737611"],"URL":"https:\/\/doi.org\/10.1145\/3737611.3776612","relation":{},"subject":[],"published":{"date-parts":[[2026,1,4]]},"assertion":[{"value":"2026-01-04","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}