{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:24:42Z","timestamp":1750220682588,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":21,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,12,3]],"date-time":"2020-12-03T00:00:00Z","timestamp":1606953600000},"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":[[2020,12,3]]},"DOI":"10.1145\/3452940.3452950","type":"proceedings-article","created":{"date-parts":[[2021,5,17]],"date-time":"2021-05-17T15:28:54Z","timestamp":1621265334000},"page":"49-54","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["PNFM"],"prefix":"10.1145","author":[{"given":"Hanzhi","family":"Xu","sequence":"first","affiliation":[{"name":"The 15th Research Institute, China Electronics Technology Group Corporation, Beijing China"}]}],"member":"320","published-online":{"date-parts":[[2021,5,17]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.169"},{"key":"e_1_3_2_1_2_1","first-page":"2407","volume-title":"ICCV","author":"Jia X.","year":"2015","unstructured":"X. Jia , E. Gavves , B. Fernando , and T. Tuytelaars . Guiding the long-short term memory model for image caption generation . In ICCV , pages 2407 -- 2415 , 2015 . X. Jia, E. Gavves, B. Fernando, and T. Tuytelaars. Guiding the long-short term memory model for image caption generation. In ICCV, pages 2407--2415, 2015."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.178"},{"key":"e_1_3_2_1_5_1","first-page":"1","volume-title":"ICLR","author":"Simonyan K.","year":"2015","unstructured":"K. Simonyan and A. Zisserman . Very deep convolutional networks for large scale image recognition . In ICLR , pages 1 -- 14 , 2015 . K. Simonyan and A. Zisserman. Very deep convolutional networks for large scale image recognition. In ICLR, pages 1--14, 2015."},{"key":"e_1_3_2_1_6_1","first-page":"2074","volume-title":"NIPS","author":"Wen W.","year":"2016","unstructured":"W. Wen , C. Wu , Y. Wang , Y. Chen , and H. Li . Learning structured sparsity in deep neural networks . In NIPS , pages 2074 -- 2082 , 2016 . W. Wen, C. Wu, Y. Wang, Y. Chen, and H. Li. Learning structured sparsity in deep neural networks. In NIPS, pages 2074--2082, 2016."},{"key":"e_1_3_2_1_7_1","first-page":"598","volume-title":"NIPS","author":"LeCun Y.","year":"1990","unstructured":"Y. LeCun , J. S. Denker , and S. A. Solla . Optimal brain damage . In NIPS , pages 598 -- 605 , 1990 . Y. LeCun, J. S. Denker, and S. A. Solla. Optimal brain damage. In NIPS, pages 598--605, 1990."},{"key":"e_1_3_2_1_8_1","first-page":"1135","volume-title":"NIPS","author":"Han S.","year":"2015","unstructured":"S. Han , J. Pool , J. Tran , and W. Dally . Learning both weights and connections for efficient neural network . In NIPS , pages 1135 -- 1143 , 2015 . S. Han, J. Pool, J. Tran, and W. Dally. Learning both weights and connections for efficient neural network. In NIPS, pages 1135--1143, 2015."},{"key":"e_1_3_2_1_9_1","first-page":"1","volume-title":"Network trimming: A data-driven neuron pruning approach towards efficient deep architectures. In arXiv preprint arXiv:1607.03250","author":"Hu H.","year":"2016","unstructured":"H. Hu , R. Peng , Y. W. Tai , and C. K. Tang . Network trimming: A data-driven neuron pruning approach towards efficient deep architectures. In arXiv preprint arXiv:1607.03250 , pages 1 -- 9 , 2016 . H. Hu, R. Peng, Y. W. Tai, and C. K. Tang. Network trimming: A data-driven neuron pruning approach towards efficient deep architectures. In arXiv preprint arXiv:1607.03250, pages 1--9, 2016."},{"key":"e_1_3_2_1_10_1","first-page":"2285","volume-title":"ICML","author":"Chen W.","year":"2015","unstructured":"W. Chen , J. Wilson , S. Tyree , K. Weinberger , and Y. Chen . Compressing neural networks with the hashing trick . In ICML , pages 2285 -- 2294 , 2015 . W. Chen, J. Wilson, S. Tyree, K. Weinberger, and Y. Chen. Compressing neural networks with the hashing trick. In ICML, pages 2285--2294, 2015."},{"key":"e_1_3_2_1_11_1","first-page":"1","volume-title":"Compressing deep convolutional networks using vector quantization. In arXiv preprint arXiv:1412.6115","author":"Gong Y.","year":"2014","unstructured":"Y. Gong , L. Liu , M. Yang , and L. Bourdev . Compressing deep convolutional networks using vector quantization. In arXiv preprint arXiv:1412.6115 , pages 1 -- 10 , 2014 . Y. Gong, L. Liu, M. Yang, and L. Bourdev. Compressing deep convolutional networks using vector quantization. In arXiv preprint arXiv:1412.6115, pages 1--10, 2014."},{"key":"e_1_3_2_1_12_1","first-page":"1","volume-title":"ICLR","author":"Han S.","year":"2016","unstructured":"S. Han , H. Mao , and W. J. Dally . Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding . In ICLR , pages 1 -- 14 , 2016 . S. Han, H. Mao, and W. J. Dally. Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding. In ICLR, pages 1--14, 2016."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.521"},{"key":"e_1_3_2_1_14_1","first-page":"1269","volume-title":"NIPS","author":"Denton E. L.","year":"2014","unstructured":"E. L. Denton , W. Zaremba , J. Bruna , Y. LeCun , and R. Fergus . Exploiting linear structure within convolutional networks for efficient evaluation . In NIPS , pages 1269 -- 1277 , 2014 . E. L. Denton, W. Zaremba, J. Bruna, Y. LeCun, and R. Fergus. Exploiting linear structure within convolutional networks for efficient evaluation. In NIPS, pages 1269--1277, 2014."},{"key":"e_1_3_2_1_15_1","first-page":"3088","volume-title":"NIPS","author":"Sindhwani V.","year":"2015","unstructured":"V. Sindhwani , T. Sainath , and S. Kumar . Structured transforms for small-footprint deep learning . In NIPS , pages 3088 -- 3096 , 2015 . V. Sindhwani, T. Sainath, and S. Kumar. Structured transforms for small-footprint deep learning. In NIPS, pages 3088--3096, 2015."},{"key":"e_1_3_2_1_16_1","first-page":"1","volume-title":"ICLR","author":"Li H.","year":"2017","unstructured":"H. Li , A. Kadav , I. Durdanovic , H. Samet , and H. P. Graf . Pruning filters for efficient ConvNets . In ICLR , pages 1 -- 13 , 2017 . H. Li, A. Kadav, I. Durdanovic, H. Samet, and H. P. Graf. Pruning filters for efficient ConvNets. In ICLR, pages 1--13, 2017."},{"key":"e_1_3_2_1_17_1","first-page":"1","volume-title":"ICLR","author":"Molchanov P.","year":"2017","unstructured":"P. Molchanov , S. Tyree , T. Karras , T. Aila , and J. Kautz . Pruning convolutional neural networks for resource efficient transfer learning . In ICLR , pages 1 -- 17 , 2017 . P. Molchanov, S. Tyree, T. Karras, T. Aila, and J. Kautz. Pruning convolutional neural networks for resource efficient transfer learning. In ICLR, pages 1--17, 2017."},{"key":"e_1_3_2_1_18_1","first-page":"1","volume-title":"Grad-CAM: Visual explanations from deep networks via gradient-based localization. In arXiv preprint arXiv:1610.02391","author":"Selvaraju R.","year":"2016","unstructured":"R. Selvaraju , M. Cogswell , A. Das , R. Vedantam , D. Parikh , and D. Batra . Grad-CAM: Visual explanations from deep networks via gradient-based localization. In arXiv preprint arXiv:1610.02391 , pages 1 -- 24 , 2016 R. Selvaraju, M. Cogswell, A. Das, R. Vedantam, D. Parikh, and D. Batra. Grad-CAM: Visual explanations from deep networks via gradient-based localization. In arXiv preprint arXiv:1610.02391, pages 1--24, 2016"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.319"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"e_1_3_2_1_22_1","first-page":"1","volume-title":"Network in network. In arXiv preprint arXiv:1312.4400","author":"Lin M.","year":"2013","unstructured":"M. Lin , Q. Chen , and S. Yan . Network in network. In arXiv preprint arXiv:1312.4400 , pages 1 -- 10 , 2013 . M. Lin, Q. Chen, and S. Yan. Network in network. In arXiv preprint arXiv:1312.4400, pages 1--10, 2013."}],"event":{"name":"ICITEE2020: The 3rd International Conference on Information Technologies and Electrical Engineering","acronym":"ICITEE2020","location":"Changde City Hunan China"},"container-title":["Proceedings of the 3rd International Conference on Information Technologies and Electrical Engineering"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3452940.3452950","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3452940.3452950","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T22:03:26Z","timestamp":1750197806000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3452940.3452950"}},"subtitle":["A Filter Level Pruning Method for CNN Compression"],"short-title":[],"issued":{"date-parts":[[2020,12,3]]},"references-count":21,"alternative-id":["10.1145\/3452940.3452950","10.1145\/3452940"],"URL":"https:\/\/doi.org\/10.1145\/3452940.3452950","relation":{},"subject":[],"published":{"date-parts":[[2020,12,3]]},"assertion":[{"value":"2021-05-17","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}