{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,16]],"date-time":"2025-10-16T06:57:27Z","timestamp":1760597847802,"version":"3.40.3"},"publisher-location":"Cham","reference-count":31,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030012601"},{"type":"electronic","value":"9783030012618"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-030-01261-8_39","type":"book-chapter","created":{"date-parts":[[2018,10,8]],"date-time":"2018-10-08T16:14:51Z","timestamp":1539015291000},"page":"657-673","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Training Binary Weight Networks via Semi-Binary Decomposition"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9458-0760","authenticated-orcid":false,"given":"Qinghao","family":"Hu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7835-4739","authenticated-orcid":false,"given":"Gang","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6384-0280","authenticated-orcid":false,"given":"Peisong","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9190-3509","authenticated-orcid":false,"given":"Yifan","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1289-2758","authenticated-orcid":false,"given":"Jian","family":"Cheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,10,6]]},"reference":[{"key":"39_CR1","doi-asserted-by":"publisher","unstructured":"Cai, Z., He, X., Sun, J., Vasconcelos, N.: Deep learning with low precision by half-wave Gaussian quantization. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition. pp. 5406\u20135414. IEEE Computer Society, Honolulu (2017). https:\/\/doi.org\/10.1109\/CVPR.2017.574","DOI":"10.1109\/CVPR.2017.574"},{"issue":"10","key":"39_CR2","doi-asserted-by":"publisher","first-page":"4730","DOI":"10.1109\/TNNLS.2017.2774288","volume":"29","author":"Jian Cheng","year":"2018","unstructured":"Cheng, J., Wu, J., Leng, C., Wang, Y., Hu, Q.: Quantized CNN: a unified approach to accelerate and compress convolutional networks. IEEE Trans. Neural Netw. Learn. Syst., 1\u201314 (2017). https:\/\/doi.org\/10.1109\/TNNLS.2017.2774288","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"issue":"1","key":"39_CR3","doi-asserted-by":"publisher","first-page":"64","DOI":"10.1631\/FITEE.1700789","volume":"19","author":"J Cheng","year":"2018","unstructured":"Cheng, J., Wang, P., Li, G., Hu, Q., Lu, H.: Recent advances in efficientcomputation of deep convolutional neural networks. Front. IT EE 19(1), 64\u201377 (2018). https:\/\/doi.org\/10.1631\/FITEE.1700789","journal-title":"Front. IT EE"},{"key":"39_CR4","unstructured":"Courbariaux, M., Bengio, Y., David, J.: Binaryconnect: training deep neural networks with binary weights during propagations. In: Cortes, C., Lawrence, N.D., Lee, D.D., Sugiyama, M., Garnett, R. (eds.) Advances in Neural Information Processing Systems 28, Montreal, Quebec, Canada, pp. 3123\u20133131 (2015)"},{"key":"39_CR5","first-page":"2148","volume-title":"Advances in Neural Information Processing Systems 26","author":"M Denil","year":"2013","unstructured":"Denil, M., Shakibi, B., Dinh, L., de Freitas, N.: Predicting parameters in deep learning. In: Burges, C.J.C., Bottou, L., Ghahramani, Z., Weinberger, K.Q. (eds.) Advances in Neural Information Processing Systems 26, pp. 2148\u20132156. Curran Associates Inc., Lake Tahoe (2013)"},{"key":"39_CR6","first-page":"1269","volume-title":"Advances in Neural Information Processing Systems 27","author":"EL Denton","year":"2014","unstructured":"Denton, E.L., Zaremba, W., Bruna, J., LeCun, Y., Fergus, R.: Exploiting linear structure within convolutional networks for efficient evaluation. In: Ghahramani, Z., Welling, M., Cortes, C., Lawrence, N.D., Weinberger, K.Q. (eds.) Advances in Neural Information Processing Systems 27, pp. 1269\u20131277. Curran Associates Inc., Montreal (2014)"},{"key":"39_CR7","doi-asserted-by":"crossref","unstructured":"Dong, Y., Ni, R., Li, J., Chen, Y., Zhu, J., Su, H.: Learning accurate low-bit deep neural networks with stochastic quantization. CoRR abs\/1708.01001 (2017). http:\/\/arxiv.org\/abs\/1708.01001","DOI":"10.5244\/C.31.189"},{"key":"39_CR8","unstructured":"Gong, Y., Liu, L., Yang, M., Bourdev, L.: Compressing deep convolutional networks using vector quantization. arXiv preprint arXiv:1412.6115 (2014)"},{"key":"39_CR9","unstructured":"Gupta, S., Agrawal, A., Gopalakrishnan, K., Narayanan, P.: Deep learning with limited numerical precision. In: Bach, F., Blei, D. (eds.) Proceedings of the 32nd International Conference on Machine Learning. Proceedings of Machine Learning Research, vol. 37, pp. 1737\u20131746. PMLR, Lille (2015)"},{"key":"39_CR10","unstructured":"Han, S., Pool, J., Tran, J., Dally, W.J.: Learning both weights and connections for efficient neural network. In: Cortes, C., Lawrence, N.D., Lee, D.D., Sugiyama, M., Garnett, R. (eds.) Advances in Neural Information Processing Systems 28, Montreal, Quebec, Canada, pp. 1135\u20131143 (2015)"},{"key":"39_CR11","first-page":"164","volume-title":"Advances in Neural Information Processing Systems 5","author":"B Hassibi","year":"1992","unstructured":"Hassibi, B., Stork, D.G.: Second order derivatives for network pruning: optimal brain surgeon. In: Hanson, S.J., Cowan, J.D., Giles, C.L. (eds.) Advances in Neural Information Processing Systems 5, pp. 164\u2013171. Morgan Kaufmann, Denver (1992)"},{"key":"39_CR12","doi-asserted-by":"crossref","unstructured":"Hu, Q., Wang, P., Cheng, J.: From hashing to CNNs: training binary weight networks via hashing. In: McIlraith, S.A., Weinberger, K.Q. (eds.) Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence. AAAI Press, New Orleans (2018)","DOI":"10.1609\/aaai.v32i1.11660"},{"key":"39_CR13","volume-title":"British Machine Vision Conference","author":"M Jaderberg","year":"2014","unstructured":"Jaderberg, M., Vedaldi, A., Zisserman, A.: Speeding up convolutional neural networks with low rank expansions. In: Valstar, M.F., French, A.P., Pridmore, T.P. (eds.) BMVC 2014. BMVA Press, Nottingham (2014)"},{"key":"39_CR14","doi-asserted-by":"publisher","unstructured":"Jia, Y., et al.: Caffe: convolutional architecture for fast feature embedding. In: Proceedings of the 22nd ACM International Conference on Multimedia, MM 2014, pp. 675\u2013678. ACM, New York (2014). https:\/\/doi.org\/10.1145\/2647868.2654889","DOI":"10.1145\/2647868.2654889"},{"key":"39_CR15","unstructured":"Kim, Y., Park, E., Yoo, S., Choi, T., Yang, L., Shin, D.: Compression of deep convolutional neural networks for fast and low power mobile applications. CoRR abs\/1511.06530 (2015). http:\/\/arxiv.org\/abs\/1511.06530"},{"issue":"6","key":"39_CR16","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1145\/3065386","volume":"60","author":"A Krizhevsky","year":"2017","unstructured":"Krizhevsky, A., Sutskever, I., Hinton, G.E.: Imagenet classification with deep convolutional neural networks. Commun. ACM 60(6), 84\u201390 (2017). https:\/\/doi.org\/10.1145\/3065386","journal-title":"Commun. ACM"},{"key":"39_CR17","unstructured":"Lebedev, V., Ganin, Y., Rakhuba, M., Oseledets, I.V., Lempitsky, V.S.: Speeding-up convolutional neural networks using fine-tuned CP-decomposition. CoRR abs\/1412.6553 (2014). http:\/\/arxiv.org\/abs\/1412.6553"},{"key":"39_CR18","doi-asserted-by":"publisher","unstructured":"Lebedev, V., Lempitsky, V.S.: Fast convnets using group-wise brain damage. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition, pp. 2554\u20132564. IEEE Computer Society, Las Vegas (2016). https:\/\/doi.org\/10.1109\/CVPR.2016.280","DOI":"10.1109\/CVPR.2016.280"},{"key":"39_CR19","first-page":"598","volume-title":"Advances in Neural Information Processing Systems 2","author":"Y LeCun","year":"1989","unstructured":"LeCun, Y., Denker, J.S., Solla, S.A.: Optimal brain damage. In: Touretzky, D.S. (ed.) Advances in Neural Information Processing Systems 2, pp. 598\u2013605. Morgan Kaufmann, Denver (1989)"},{"key":"39_CR20","unstructured":"Lin, D., Talathi, S., Annapureddy, S.: Fixed point quantization of deep convolutional networks. In: Balcan, M.F., Weinberger, K.Q. (eds.) Proceedings of the 33rd International Conference on Machine Learning. Proceedings of Machine Learning Research, vol. 48, pp. 2849\u20132858. PMLR, New York (2016)"},{"key":"39_CR21","doi-asserted-by":"publisher","unstructured":"Long, J., Shelhamer, E., Darrell, T.: Fully convolutional networks for semantic segmentation. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015, Boston, MA, USA, 7\u201312 June 2015, pp. 3431\u20133440. IEEE Computer Society (2015). https:\/\/doi.org\/10.1109\/CVPR.2015.7298965","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"39_CR22","doi-asserted-by":"publisher","unstructured":"Qiu, J., et al.: Going deeper with embedded FPGA platform for convolutional neural network. In: Chen, D., Greene, J.W. (eds.) Proceedings of the 2016 ACM\/SIGDA International Symposium on Field-Programmable Gate Arrays, FPGA 2016, pp. 26\u201335. ACM, New York (2016). https:\/\/doi.org\/10.1145\/2847263.2847265","DOI":"10.1145\/2847263.2847265"},{"key":"39_CR23","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"525","DOI":"10.1007\/978-3-319-46493-0_32","volume-title":"Computer Vision \u2013 ECCV 2016","author":"M Rastegari","year":"2016","unstructured":"Rastegari, M., Ordonez, V., Redmon, J., Farhadi, A.: XNOR-Net: imagenet classification using binary convolutional neural networks. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9908, pp. 525\u2013542. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46493-0_32"},{"issue":"6","key":"39_CR24","doi-asserted-by":"publisher","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","volume":"39","author":"S Ren","year":"2017","unstructured":"Ren, S., He, K., Girshick, R.B., Sun, J.: Faster R-CNN: towards real-time object detection with region proposal networks. IEEE Trans. Pattern Anal. Mach. Intell. 39(6), 1137\u20131149 (2017). https:\/\/doi.org\/10.1109\/TPAMI.2016.2577031","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"39_CR25","doi-asserted-by":"publisher","unstructured":"Wang, P., Cheng, J.: Accelerating convolutional neural networks for mobile applications. In: Proceedings of the 2016 ACM on Multimedia Conference, MM 2016, pp. 541\u2013545. ACM, New York (2016). https:\/\/doi.org\/10.1145\/2964284.2967280","DOI":"10.1145\/2964284.2967280"},{"key":"39_CR26","doi-asserted-by":"publisher","unstructured":"Wang, P., Cheng, J.: Fixed-point factorized networks. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017, Honolulu, HI, USA, 21\u201326 July 2017, pp. 3966\u20133974. IEEE Computer Society (2017). https:\/\/doi.org\/10.1109\/CVPR.2017.422","DOI":"10.1109\/CVPR.2017.422"},{"key":"39_CR27","doi-asserted-by":"crossref","unstructured":"Wang, P., Hu, Q., Zhang, Y., Zhang, C., Liu, Y., Cheng, J.: Two-step quantization for low-bit neural networks. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society (2018)","DOI":"10.1109\/CVPR.2018.00460"},{"key":"39_CR28","doi-asserted-by":"publisher","unstructured":"Wu, J., Leng, C., Wang, Y., Hu, Q., Cheng, J.: Quantized convolutional neuralnetworks for mobile devices. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 4820\u20134828. IEEE Computer Society, LasVegas (2016). https:\/\/doi.org\/10.1109\/CVPR.2016.521","DOI":"10.1109\/CVPR.2016.521"},{"key":"39_CR29","doi-asserted-by":"publisher","unstructured":"Zhang, C., Li, P., Sun, G., Guan, Y., Xiao, B., Cong, J.: Optimizing FPGA-based accelerator design for deep convolutional neural networks. In: Constantinides, G.A., Chen, D. (eds.) Proceedings of the 2015 ACM\/SIGDA International Symposium on Field-Programmable Gate Arrays, pp. 161\u2013170. ACM, Monterey (2015). https:\/\/doi.org\/10.1145\/2684746.2689060","DOI":"10.1145\/2684746.2689060"},{"issue":"10","key":"39_CR30","doi-asserted-by":"publisher","first-page":"1943","DOI":"10.1109\/TPAMI.2015.2502579","volume":"38","author":"X Zhang","year":"2016","unstructured":"Zhang, X., Zou, J., He, K., Sun, J.: Accelerating very deep convolutional networks for classification and detection. IEEE Trans. Pattern Anal. Mach. Intell. 38(10), 1943\u20131955 (2016). https:\/\/doi.org\/10.1109\/TPAMI.2015.2502579","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"39_CR31","unstructured":"Zhou, S., Ni, Z., Zhou, X., Wen, H., Wu, Y., Zou, Y.: DoReFa-Net: training low bitwidth convolutional neural networks with low bitwidth gradients. CoRR abs\/1606.06160 (2016). http:\/\/arxiv.org\/abs\/1606.06160"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2018"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-01261-8_39","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,8]],"date-time":"2022-10-08T00:41:41Z","timestamp":1665189701000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-01261-8_39"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783030012601","9783030012618"],"references-count":31,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-01261-8_39","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"6 October 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Computer Vision","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Munich","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Germany","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 September 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 September 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv2018.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}