{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T18:35:54Z","timestamp":1730313354843,"version":"3.28.0"},"reference-count":17,"publisher":"SPIE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,4,3]]},"DOI":"10.1117\/12.3023264","type":"proceedings-article","created":{"date-parts":[[2024,4,3]],"date-time":"2024-04-03T16:49:17Z","timestamp":1712162957000},"page":"11","source":"Crossref","is-referenced-by-count":0,"title":["Training of binary neural network models using continuous approximation"],"prefix":"10.1117","author":[{"given":"Dmitrij","family":"Pavliuchenkov","sequence":"first","affiliation":[]},{"given":"Anton","family":"Trusov","sequence":"additional","affiliation":[]},{"given":"Elena","family":"Limonova","sequence":"additional","affiliation":[]}],"member":"189","reference":[{"doi-asserted-by":"publisher","key":"c1","DOI":"10.1109\/Access.6287639"},{"key":"c2","first-page":"415","article-title":"Deep neural networks for moving object classification in video surveillance applications,","volume-title":"in Fourteenth International Conference on Machine Vision (ICMV 2021)","volume":"12084","author":"Boukhriss","year":"2022"},{"key":"c3","doi-asserted-by":"crossref","first-page":"422","DOI":"10.1117\/12.2624371","article-title":"Virtual restoration of paintings based on deep learning,","volume-title":"in Fourteenth International Conference on Machine Vision (ICMV 2021)","volume":"12084","author":"Sizyakin","year":"2022"},{"doi-asserted-by":"publisher","key":"c4","DOI":"10.18287\/2412-6179-CO-1016"},{"doi-asserted-by":"publisher","key":"c5","DOI":"10.1016\/j.eswa.2021.115406"},{"doi-asserted-by":"publisher","key":"c6","DOI":"10.14357\/20718632220201"},{"key":"c7","first-page":"25553","article-title":"Learning frequency domain approximation for binary neural networks,","volume":"34","author":"Xu","year":"2021","journal-title":"Advances in Neural Information Processing Systems"},{"doi-asserted-by":"publisher","key":"c8","DOI":"10.1016\/j.patcog.2020.107281"},{"key":"c9","article-title":"Binarized neural networks: Training deep neural networks with weights and activations constrained to + 1 or -1,","author":"Courbariaux","year":"2016","journal-title":"arXiv preprint arXiv:1602.02830"},{"year":"2018","author":"Darabi","article-title":"BNN+: Improved binary network training,","key":"c10"},{"issue":"1","key":"c11","article-title":"How to train a compact binary neural network with high accuracy?,","volume-title":"in Proceedings of the AAAI conference on artificial intelligence","volume":"31","author":"Tang","year":"2017"},{"key":"c12","article-title":"Expectation backpropagation: Parameter-free training of multilayer neural networks with continuous or discrete weights,","volume":"27","author":"Soudry","year":"2014","journal-title":"Advances in neural information processing systems"},{"key":"c13","article-title":"An introduction to convolutional neural networks,","author":"O\u2019Shea","year":"2015","journal-title":"arXiv preprint arXiv:1511.08458"},{"key":"c14","article-title":"Incremental network quantization: Towards lossless CNNs with low-precision weights,","author":"Zhou","year":"2017","journal-title":"arXiv preprint arXiv:1702.03044"},{"year":"2010","author":"LeCun","article-title":"Mnist handwritten digit database","key":"c15"},{"key":"c16","article-title":"Adam: A method for stochastic optimization,","author":"Kingma","year":"2014","journal-title":"arXiv preprint arXiv:1412.6980"},{"doi-asserted-by":"publisher","key":"c17","DOI":"10.1109\/5.726791"}],"event":{"name":"Sixteenth International Conference on Machine Vision (ICMV 2023)","start":{"date-parts":[[2023,11,15]]},"location":"Yerevan, Armenia","end":{"date-parts":[[2023,11,18]]}},"container-title":["Sixteenth International Conference on Machine Vision (ICMV 2023)"],"original-title":[],"deposited":{"date-parts":[[2024,5,24]],"date-time":"2024-05-24T22:23:20Z","timestamp":1716589400000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.spiedigitallibrary.org\/conference-proceedings-of-spie\/13072\/3023264\/Training-of-binary-neural-network-models-using-continuous-approximation\/10.1117\/12.3023264.full"}},"subtitle":[],"editor":[{"given":"Wolfgang","family":"Osten","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2024,4,3]]},"references-count":17,"URL":"https:\/\/doi.org\/10.1117\/12.3023264","relation":{},"subject":[],"published":{"date-parts":[[2024,4,3]]}}}