Object Detection Algorithm Based on Improved Feature Extraction Network

Ting Qiao; Hansong Su; Gaohua Liu; Meng Wang

doi:10.3788/LOP56.231008

[1] He Z C, Zhao L Z, Chen C. Convolution neural network with multi-resolution feature fusion for facial expression recognition[J]. Laser & Optoelectronics Progress, 55, 071503(2018).

[2] Chen Y, Fan R S, Wang J X et al. Cloud detection of ZY-3 satellite remote sensing images based on deep learning[J]. Acta Optica Sinica, 38, 0128005(2018).

[3] Girshick R, Donahue J, Darrell T et al. Rich feature hierarchies for accurate object detection and semantic segmentation. [C]∥2014 IEEE Conference on Computer Vision and Pattern Recognition, June 23-28, 2014, Columbus, OH, USA. New York: IEEE, 580-587(2014).

[4] Girshick R. Fast R-CNN. [C]∥2015 IEEE International Conference on Computer Vision (ICCV), December 7-13, 2015, Santiago, Chile. New York: IEEE, 1440-1448(2015).

[5] Ren S Q, He K M, Girshick R et al. Faster R-CNN: towards real-time object detection with region proposal networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39, 1137-1149(2017).

[6] Redmon J, Divvala S, Girshick R et al. You only look once: unified, real-time object detection. [C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA. New York: IEEE, 779-788(2016).

[7] Liu W, Anguelov D, Erhan D et al. SSD: single shot MultiBox detector[M]. ∥Leibe B, Matas J, Sebe N, et al. Computer vision-ECCV 2016. Lecture notes in computer science. Cham: Springer, 9905, 21-37(2016).

[8] Chen L L, Zhang Z D, Peng L. Real-time detection based on improved single shot MultiBox detector[J]. Laser & Optoelectronics Progress, 56, 011002(2019).

[9] Dai J F, Li Y, He K M et al. R-FCN: object detection via region-based fully convolutional networks. [C]∥Proceedings of the 30th International Conference on Neural Information Processing Systems, December 5-10, 2016, Barcelona, Spain. New York: ACM, 379-387(2016).

[10] Cai Y Z, Yang D D, Mao N et al. Visual tracking algorithm based on adaptive convolutional features[J]. Acta Optica Sinica, 37, 0315002(2017).

[11] Krizhevsky A, Sutskever I, Hinton G E. ImageNet classification with deep convolutional neural networks. [C]∥Proceedings of the 25th International Conference on Neural Information Processing Systems, December 3-6, 2012, Lake Tahoe, Nevada. New York: ACM, 1097-1105(2012).

[12] Huang G. Liu Z, van der Maaten L, et al. Densely connected convolutional networks. [C]∥2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 2261-2269(2017).

[13] He K M, Zhang X Y, Ren S Q et al. Deep residual learning for image recognition. [C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA. New York: IEEE, 770-778(2016).

[14] Neubeck A, van Gool L. Efficient non-maximum suppression. [C]∥18th International Conference on Pattern Recognition (ICPR'06), August 20-24, 2006, Hong Kong, China. New York: IEEE, 9210072(2006).