{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:28:14Z","timestamp":1750220894216,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":21,"publisher":"ACM","license":[{"start":{"date-parts":[[2019,12,20]],"date-time":"2019-12-20T00:00:00Z","timestamp":1576800000000},"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":[[2019,12,20]]},"DOI":"10.1145\/3376067.3376106","type":"proceedings-article","created":{"date-parts":[[2020,2,26]],"date-time":"2020-02-26T07:38:38Z","timestamp":1582702718000},"page":"173-177","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Self-supervised Image Classification based on the Distances of Deep Feature Space"],"prefix":"10.1145","author":[{"given":"Zhuoxun","family":"He","sequence":"first","affiliation":[{"name":"Shanghai Jiao Tong University, Shanghai, China"}]},{"given":"Ya","family":"Zhang","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University, Shanghai, China"}]},{"given":"Yanfeng","family":"Wang","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University, Shanghai, China"}]}],"member":"320","published-online":{"date-parts":[[2020,2,25]]},"reference":[{"volume-title":"International Conference on Learning Representations.","author":"Zhang H.","unstructured":"Zhang , H. , Cisse , M. , Dauphin , Y. N. , and Lopez-Paz , D . 2017. mixup: Beyond empirical risk minimization . In International Conference on Learning Representations. Zhang, H., Cisse, M., Dauphin, Y. N., and Lopez-Paz, D. 2017. mixup: Beyond empirical risk minimization. In International Conference on Learning Representations.","key":"e_1_3_2_1_1_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_2_1","DOI":"10.1007\/s11263-015-0816-y"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_3_1","DOI":"10.5555\/2627435.2670313"},{"volume-title":"Inernational Conference on Machine Learning.","author":"Ioffe S.","unstructured":"Ioffe , S. and Szegedy , C . 2015. Batch normalization: Accelerating deep network training by reducing internal covariate shift . In Inernational Conference on Machine Learning. Ioffe, S. and Szegedy, C. 2015. Batch normalization: Accelerating deep network training by reducing internal covariate shift. In Inernational Conference on Machine Learning.","key":"e_1_3_2_1_4_1"},{"volume-title":"the AAAI Conference on Artificial Intelligence.","author":"Guo H.","unstructured":"Guo , H. , Mao , Y. , and Zhang , R . 2019. Mixup as locally linear out-of-manifold regularization . In the AAAI Conference on Artificial Intelligence. Guo, H., Mao, Y., and Zhang, R. 2019. Mixup as locally linear out-of-manifold regularization. In the AAAI Conference on Artificial Intelligence.","key":"e_1_3_2_1_5_1"},{"volume-title":"International Conference on Machine Learning.","author":"Verma V.","unstructured":"Verma , V. , Lamb , A. , Beckham , C. , Najafi , A. , Mitliagkas , I. , Lopez-Paz , D. , and Bengio , Y . 2019. Manifold mixup: Better representations by interpolating hidden states . In International Conference on Machine Learning. Verma, V., Lamb, A., Beckham, C., Najafi, A., Mitliagkas, I., Lopez-Paz, D., and Bengio, Y. 2019. Manifold mixup: Better representations by interpolating hidden states. In International Conference on Machine Learning.","key":"e_1_3_2_1_6_1"},{"volume-title":"the IEEE Conference on Computer Vision and Pattern Recognition, 6090--6099","author":"Upchurch P.","unstructured":"Upchurch , P. , Gardner , J. R. , Pleiss , G. , Pless , R. , Snavely , N. , Bala , K. and Weinberger , K. Q . 2017. Deep feature interpolation for image content changes . In the IEEE Conference on Computer Vision and Pattern Recognition, 6090--6099 . Upchurch, P., Gardner, J. R., Pleiss, G., Pless, R., Snavely, N., Bala, K. and Weinberger, K. Q. 2017. Deep feature interpolation for image content changes. In the IEEE Conference on Computer Vision and Pattern Recognition, 6090--6099.","key":"e_1_3_2_1_7_1"},{"volume-title":"European Conference on Computer Vision, 499--515","author":"Wen Y.","unstructured":"Wen , Y. , Zhang , K. , Li , Z. and Qiao , Y . 2016. A discriminative feature learning approach for deep face recognition . In European Conference on Computer Vision, 499--515 . Wen, Y., Zhang, K., Li, Z. and Qiao, Y. 2016. A discriminative feature learning approach for deep face recognition. In European Conference on Computer Vision, 499--515.","key":"e_1_3_2_1_8_1"},{"unstructured":"Krizhevsky A.; Sutskever I.; and Hinton G. E. 2012. Imagenet classification with deep convolutional neural networks. In Advances in neural information processing systems.  Krizhevsky A.; Sutskever I.; and Hinton G. E. 2012. Imagenet classification with deep convolutional neural networks. In Advances in neural information processing systems.","key":"e_1_3_2_1_9_1"},{"volume-title":"the IEEE Conference on Computer Vision and Pattern Recognition.","author":"Szegedy C.","unstructured":"Szegedy , C. ; Liu , W. ; Jia , Y. ; Sermanet , P. ; Reed , S. ; Anguelov , D. ; Erhan , D. ; Vanhoucke , V. ; and Rabinovich , A . 2015. Going deeper with convolutions . In the IEEE Conference on Computer Vision and Pattern Recognition. Szegedy, C.; Liu, W.; Jia, Y.; Sermanet, P.; Reed, S.; Anguelov, D.; Erhan, D.; Vanhoucke, V.; and Rabinovich, A. 2015. Going deeper with convolutions. In the IEEE Conference on Computer Vision and Pattern Recognition.","key":"e_1_3_2_1_10_1"},{"volume-title":"the IEEE Conference on Computer Vision and Pattern Recognition.","author":"Ciregan D.","unstructured":"Ciregan , D. ; Meier , U. ; and Schmidhuber , J . 2012. Multicolumn deep neural networks for image classification . In the IEEE Conference on Computer Vision and Pattern Recognition. Ciregan, D.; Meier, U.; and Schmidhuber, J. 2012. Multicolumn deep neural networks for image classification. In the IEEE Conference on Computer Vision and Pattern Recognition.","key":"e_1_3_2_1_11_1"},{"key":"e_1_3_2_1_12_1","volume-title":"Apac: Augmented pattern classification with neural networks. arXiv preprint arXiv:1505.03229.","author":"Sato I.","year":"2015","unstructured":"Sato , I. ; Nishimura , H. ; and Yokoi , K . 2015 . Apac: Augmented pattern classification with neural networks. arXiv preprint arXiv:1505.03229. Sato, I.; Nishimura, H.; and Yokoi, K. 2015. Apac: Augmented pattern classification with neural networks. arXiv preprint arXiv:1505.03229."},{"volume-title":"the IEEE Conference on Computer Vision and Pattern Recognition.","author":"He T.","unstructured":"He , T. ; Zhang , Z. ; Zhang , H. ; Zhang , Z. ; Xie , J. ; and Li , M . 2019. Bag of tricks for image classification with convolutional neural networks . In the IEEE Conference on Computer Vision and Pattern Recognition. He, T.; Zhang, Z.; Zhang, H.; Zhang, Z.; Xie, J.; and Li, M. 2019. Bag of tricks for image classification with convolutional neural networks. In the IEEE Conference on Computer Vision and Pattern Recognition.","key":"e_1_3_2_1_13_1"},{"volume-title":"International Conference on Computer Vision.","author":"Yun S.","unstructured":"Yun , S. ; Han , D. ; Oh , S. J. ; Chun , S. ; Choe , J. ; and Yoo , Y . 2019. Cutmix: Regularization strategy to train strong classifiers with localizable features . In International Conference on Computer Vision. Yun, S.; Han, D.; Oh, S. J.; Chun, S.; Choe, J.; and Yoo, Y. 2019. Cutmix: Regularization strategy to train strong classifiers with localizable features. In International Conference on Computer Vision.","key":"e_1_3_2_1_14_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_15_1","DOI":"10.1109\/ACCESS.2017.2696121"},{"unstructured":"Tran T.; Pham T.; Carneiro G.; Palmer L.; and Reid I. 2017. A bayesian data augmentation approach for learning deep models. In Advances in neural information processing systems.  Tran T.; Pham T.; Carneiro G.; Palmer L.; and Reid I. 2017. A bayesian data augmentation approach for learning deep models. In Advances in neural information processing systems.","key":"e_1_3_2_1_16_1"},{"volume-title":"the IEEE Conference on Computer Vision and Pattern Recognition.","author":"Cubuk E. D.","unstructured":"Cubuk , E. D. ; Zoph , B. ; Mane , D. ; Vasudevan , V. ; and Le , Q. V . 2019. Autoaugment: Learning augmentation strategies from data . In the IEEE Conference on Computer Vision and Pattern Recognition. Cubuk, E. D.; Zoph, B.; Mane, D.; Vasudevan, V.; and Le, Q. V. 2019. Autoaugment: Learning augmentation strategies from data. In the IEEE Conference on Computer Vision and Pattern Recognition.","key":"e_1_3_2_1_17_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_18_1","DOI":"10.1007\/978-1-4757-3264-1"},{"unstructured":"Chapelle O. Weston J. Bottou L. and Vapnik V. 2000. Vicinal risk minimization. In Advances in neural information processing systems.  Chapelle O. Weston J. Bottou L. and Vapnik V. 2000. Vicinal risk minimization. In Advances in neural information processing systems.","key":"e_1_3_2_1_19_1"},{"volume-title":"European conference on computer vision, 630--645","author":"He K.","unstructured":"He , K. , Zhang , X. , Ren , S. and Sun , J . 2016. Identity mappings in deep residual networks . In European conference on computer vision, 630--645 . He, K., Zhang, X., Ren, S. and Sun, J. 2016. Identity mappings in deep residual networks. In European conference on computer vision, 630--645.","key":"e_1_3_2_1_20_1"},{"volume-title":"Proceedings of the British Machine Vision Conference.","author":"Zagoruyko S.","unstructured":"Zagoruyko , S. and Komodakis , N . 2016. Wide residual networks . In Proceedings of the British Machine Vision Conference. Zagoruyko, S. and Komodakis, N. 2016. Wide residual networks. In Proceedings of the British Machine Vision Conference.","key":"e_1_3_2_1_21_1"}],"event":{"sponsor":["Shanghai Jiao Tong University Shanghai Jiao Tong University","Xidian University","TU Tianjin University"],"acronym":"ICVIP 2019","name":"ICVIP 2019: 2019 the 3rd International Conference on Video and Image Processing","location":"Shanghai China"},"container-title":["Proceedings of the 3rd International Conference on Video and Image Processing"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3376067.3376106","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3376067.3376106","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T23:44:34Z","timestamp":1750203874000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3376067.3376106"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,12,20]]},"references-count":21,"alternative-id":["10.1145\/3376067.3376106","10.1145\/3376067"],"URL":"https:\/\/doi.org\/10.1145\/3376067.3376106","relation":{},"subject":[],"published":{"date-parts":[[2019,12,20]]},"assertion":[{"value":"2020-02-25","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}