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In Proceedings of the 27th International Conference on Neural Information Processing Systems - Volume 2 (NIPS'14). MIT Press, Cambridge, MA, USA, 2204--2212."},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00166"},{"volume-title":"2015 International Conference on Hardware\/Software Codesign and System Synthesis (CODES+ISSS). 124--132","author":"Park E.","key":"e_1_3_2_1_31_1","unstructured":"E. Park , D. Kim , S. Kim , Y. D. Kim , G. Kim , S. Yoon , and S. Yoo . 2015. Big\/little deep neural network for ultra low power inference . In 2015 International Conference on Hardware\/Software Codesign and System Synthesis (CODES+ISSS). 124--132 . E. Park, D. Kim, S. Kim, Y. D. Kim, G. Kim, S. Yoon, and S. Yoo. 2015. Big\/little deep neural network for ultra low power inference. In 2015 International Conference on Hardware\/Software Codesign and System Synthesis (CODES+ISSS). 124--132."},{"key":"e_1_3_2_1_32_1","volume-title":"On Learning Where To Look. 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CoRR abs\/1804.02767 (2018). arXiv:1804.02767 http:\/\/arxiv.org\/abs\/1804.02767"},{"volume-title":"Advances in Neural Information Processing Systems 28","author":"Ren Shaoqing","key":"e_1_3_2_1_36_1","unstructured":"Shaoqing Ren , Kaiming He , Ross Girshick , and Jian Sun . 2015. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks . In Advances in Neural Information Processing Systems 28 , C. Cortes, N. D. Lawrence, D. D. Lee, M. Sugiyama, and R. Garnett (Eds.). Curran Associates, Inc. , 91--99. Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun. 2015. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks. In Advances in Neural Information Processing Systems 28, C. Cortes, N. D. Lawrence, D. D. Lee, M. Sugiyama, and R. Garnett (Eds.). 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Object Detection in Videos by Short and Long Range Object Linking. CoRR abs\/1801.09823 (2018). arXiv:1801.09823 http:\/\/arxiv.org\/abs\/1801.09823"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/2744769.2744904"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/2627369.2627613"},{"key":"e_1_3_2_1_42_1","volume-title":"Advances in Neural Information Processing Systems 29","author":"Wen Wei","year":"2074","unstructured":"Wei Wen , Chunpeng Wu , Yandan Wang , Yiran Chen , and Hai Li. 2016. Learning Structured Sparsity in Deep Neural Networks . In Advances in Neural Information Processing Systems 29 , D. D. Lee, M. Sugiyama, U. V. Luxburg, I. Guyon, and R. Garnett (Eds.). Curran Associates, Inc. , 2074 --2082. http:\/\/papers.nips.cc\/paper\/6504-learning-structured-sparsity-in-deep-neural-networks.pdf Wei Wen, Chunpeng Wu, Yandan Wang, Yiran Chen, and Hai Li. 2016. Learning Structured Sparsity in Deep Neural Networks. In Advances in Neural Information Processing Systems 29, D. D. Lee, M. Sugiyama, U. V. Luxburg, I. Guyon, and R. Garnett (Eds.). Curran Associates, Inc., 2074--2082. http:\/\/papers.nips.cc\/paper\/6504-learning-structured-sparsity-in-deep-neural-networks.pdf"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.534"},{"key":"e_1_3_2_1_44_1","volume-title":"Towards High Performance Video Object Detection. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR).","author":"Zhu Xizhou","year":"2018","unstructured":"Xizhou Zhu , Jifeng Dai , Lu Yuan , and Yichen Wei . 2018 . Towards High Performance Video Object Detection. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Xizhou Zhu, Jifeng Dai, Lu Yuan, and Yichen Wei. 2018. Towards High Performance Video Object Detection. 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