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Springer, Cham, 2016: 21-37."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"crossref","unstructured":"Redmon J Divvala S Girshick R You only look once: Unified real-time object detection[C]\/\/Proceedings of the IEEE conference on computer vision and pattern recognition. 2016: 779-788.  Redmon J Divvala S Girshick R You only look once: Unified real-time object detection[C]\/\/Proceedings of the IEEE conference on computer vision and pattern recognition. 2016: 779-788.","DOI":"10.1109\/CVPR.2016.91"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"crossref","unstructured":"Redmon J Farhadi A. YOLO9000: better faster stronger[C]\/\/Proceedings of the IEEE conference on computer vision and pattern recognition. 2017: 7263-7271.  Redmon J Farhadi A. YOLO9000: better faster stronger[C]\/\/Proceedings of the IEEE conference on computer vision and pattern recognition. 2017: 7263-7271.","DOI":"10.1109\/CVPR.2017.690"},{"key":"e_1_3_2_1_13_1","volume-title":"Yolov3: An incremental improvement[EB]. arXiv preprint arXiv:1804.02767","author":"Redmon J","year":"2018","unstructured":"Redmon J , Farhadi A. Yolov3: An incremental improvement[EB]. arXiv preprint arXiv:1804.02767 , 2018 . Redmon J, Farhadi A. Yolov3: An incremental improvement[EB]. arXiv preprint arXiv:1804.02767, 2018."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"crossref","unstructured":"Girshick R Donahue J Darrell T Rich feature hierarchies for accurate object detection and semantic segmentation[C]\/\/Proceedings of the IEEE conference on computer vision and pattern recognition. 2014: 580-587.  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Fast r-cnn[C]\/\/Proceedings of the IEEE international conference on computer vision. 2015: 1440-1448.","DOI":"10.1109\/ICCV.2015.169"},{"key":"e_1_3_2_1_17_1","volume-title":"Faster r-cnn: Towards real-time object detection with region proposal networks[EB]. arXiv preprint arXiv:1506.01497","author":"Ren S","year":"2015","unstructured":"Ren S , He K , Girshick R , Faster r-cnn: Towards real-time object detection with region proposal networks[EB]. arXiv preprint arXiv:1506.01497 , 2015 . Ren S, He K, Girshick R, Faster r-cnn: Towards real-time object detection with region proposal networks[EB]. arXiv preprint arXiv:1506.01497, 2015."},{"key":"e_1_3_2_1_18_1","volume-title":"He K","author":"Dai J","year":"2016","unstructured":"Dai J , Li Y , He K , R-fcn : Object de tection via region-based fully convolutional networks[EB]. arXiv preprint arXiv:1605.06409, 2016 . Dai J, Li Y, He K, R-fcn: Object detection via region-based fully convolutional networks[EB]. arXiv preprint arXiv:1605.06409, 2016."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"crossref","unstructured":"He K Gkioxari G Doll\u00e1r P Mask r-cnn[C]\/\/Proceedings of the IEEE international conference on computer vision. 2017: 2961-2969.  He K Gkioxari G Doll\u00e1r P Mask r-cnn[C]\/\/Proceedings of the IEEE international conference on computer vision. 2017: 2961-2969.","DOI":"10.1109\/ICCV.2017.322"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"crossref","unstructured":"Lin T Y Goyal P Girshick R Focal loss for dense object detection[C]\/\/Proceedings of the IEEE international conference on computer vision. 2017: 2980-2988.  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Liu S Qi L Qin H Path aggregation network for instance segmentation[C]\/\/Proceedings of the IEEE conference on computer vision and pattern recognition. 2018: 8759-8768.","DOI":"10.1109\/CVPR.2018.00913"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"crossref","unstructured":"Kim S W Kook H K Sun J Y Parallel feature pyramid network for object detection[C]\/\/Proceedings of the European Conference on Computer Vision. 2018: 234-250.  Kim S W Kook H K Sun J Y Parallel feature pyramid network for object detection[C]\/\/Proceedings of the European Conference on Computer Vision. 2018: 234-250.","DOI":"10.1007\/978-3-030-01228-1_15"},{"key":"e_1_3_2_1_24_1","volume-title":"M2det: A single-shot object detector based on multi-level feature pyramid network[C]\/\/Proceedings of the AAAI conference on artificial intelligence","author":"Zhao Q","year":"2019","unstructured":"Zhao Q , Sheng T , Wang Y , M2det: A single-shot object detector based on multi-level feature pyramid network[C]\/\/Proceedings of the AAAI conference on artificial intelligence . 2019 , 33(01): 9259-9266. Zhao Q, Sheng T, Wang Y, M2det: A single-shot object detector based on multi-level feature pyramid network[C]\/\/Proceedings of the AAAI conference on artificial intelligence. 2019, 33(01): 9259-9266."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"crossref","unstructured":"Ghiasi G Lin T Y Le Q V. Nas-fpn: Learning scalable feature pyramid architecture for object detection[C]\/\/Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 2019: 7036-7045.  Ghiasi G Lin T Y Le Q V. Nas-fpn: Learning scalable feature pyramid architecture for object detection[C]\/\/Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 2019: 7036-7045.","DOI":"10.1109\/CVPR.2019.00720"},{"key":"e_1_3_2_1_26_1","volume-title":"Learning spatial fusion for single-shot object detection[EB]. arXiv preprint arXiv:1911.09516","author":"Liu S","year":"2019","unstructured":"Liu S , Huang D , Wang Y. Learning spatial fusion for single-shot object detection[EB]. arXiv preprint arXiv:1911.09516 , 2019 . Liu S, Huang D, Wang Y. Learning spatial fusion for single-shot object detection[EB]. arXiv preprint arXiv:1911.09516, 2019."},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"crossref","unstructured":"Tan M Pang R Le Q V. Efficientdet: Scalable and efficient object detection[C]\/\/Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition. 2020: 10781-10790.  Tan M Pang R Le Q V. Efficientdet: Scalable and efficient object detection[C]\/\/Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition. 2020: 10781-10790.","DOI":"10.1109\/CVPR42600.2020.01079"},{"key":"e_1_3_2_1_28_1","volume-title":"Zhang Q","author":"Guo C","year":"2020","unstructured":"Guo C , Fan B , Zhang Q , Augfpn : Improving multi-scale feature learning for object detection[C]\/\/Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition . 2020 : 12595-12604. Guo C, Fan B, Zhang Q, Augfpn: Improving multi-scale feature learning for object detection[C]\/\/Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 2020: 12595-12604."},{"volume-title":"PMLR","author":"Tan M","key":"e_1_3_2_1_29_1","unstructured":"Tan M , Le Q. Efficientnet : Rethinking model scaling for convolutional neural networks[C]\/\/International Conference on Machine Learning . PMLR , 2019: 6105-6114. Tan M, Le Q. Efficientnet: Rethinking model scaling for convolutional neural networks[C]\/\/International Conference on Machine Learning. PMLR, 2019: 6105-6114."},{"volume-title":"PMLR","author":"Loffe S","key":"e_1_3_2_1_30_1","unstructured":"Loffe S , Szegedy C. Batch normalization : Accelerating deep network training by reducing internal covariate shift[C]\/\/International conference on machine learning . PMLR , 2015: 448-456. Loffe S, Szegedy C. Batch normalization: Accelerating deep network training by reducing internal covariate shift[C]\/\/International conference on machine learning. PMLR, 2015: 448-456."},{"key":"e_1_3_2_1_31_1","volume-title":"Searching for activation functions[EB]. arXiv preprint arXiv:1710.05941","author":"Ramachandran P","year":"2017","unstructured":"Ramachandran P , Zoph B , Le Q V . Searching for activation functions[EB]. arXiv preprint arXiv:1710.05941 , 2017 . Ramachandran P, Zoph B, Le Q V. Searching for activation functions[EB]. arXiv preprint arXiv:1710.05941, 2017."},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"crossref","unstructured":"Chollet F. Xception: Deep learning with depthwise separable convolutions[C]\/\/Proceedings of the IEEE conference on computer vision and pattern recognition. 2017: 1251-1258.  Chollet F. Xception: Deep learning with depthwise separable convolutions[C]\/\/Proceedings of the IEEE conference on computer vision and pattern recognition. 2017: 1251-1258.","DOI":"10.1109\/CVPR.2017.195"},{"volume-title":"JMLR Workshop and Conference Proceedings","author":"Glorot X","key":"e_1_3_2_1_33_1","unstructured":"Glorot X , Bordes A , Bengio Y. Deep sparse rectifier neural networks[C]\/\/Proceedings of the fourteenth international conference on artificial intelligence and statistics . JMLR Workshop and Conference Proceedings , 2011: 315-323. Glorot X, Bordes A, Bengio Y. Deep sparse rectifier neural networks[C]\/\/Proceedings of the fourteenth international conference on artificial intelligence and statistics. JMLR Workshop and Conference Proceedings, 2011: 315-323."},{"key":"e_1_3_2_1_34_1","volume-title":"Microsoft coco: Common objects in context[C]\/\/European conference on computer vision","author":"Lin T Y","year":"2014","unstructured":"Lin T Y , Maire M , Belongie S , Microsoft coco: Common objects in context[C]\/\/European conference on computer vision . Springer , Cham , 2014 : 740-755. Lin T Y, Maire M, Belongie S, Microsoft coco: Common objects in context[C]\/\/European conference on computer vision. 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