[1] 茹晓青, 华国光, 李丽宏, 等. 基于形变卷积神经网络的手写体数字识别研究[J]. 微电子学与计算机, 2019, 36(4): 47-51.

    Ru X Q, Hua G G, Li L H, et al. Handwritten digital recognition based on deformable convolutional neural network[J]. Microelectronics & Computer, 2019, 36(4): 47-51.

[2] 杜薇, 周武能. 基于CTC模型的无分割文本验证码识别[J]. 计算机与现代化, 2018( 9): 48- 51.

    DuW, Zhou WN. Recognition of non-segmented text verification code based on CTC model[J]. Computer and Modernization, 2018( 9): 48- 51.

[3] Breuel TM. Segmentation of handprinted letter strings using a dynamic programming algorithm[C]∥Proceedings of Sixth International Conference on Document Analysis and Recognition, September 13, 2001, Seattle, WA, USA. New York: IEEE, 2001: 821- 826.

[4] Li Y X, Tan C L, Ding X Q, et al. Contextual post-processing based on the confusion matrix in offline handwritten Chinese script recognition[J]. Pattern Recognition, 2004, 37(9): 1901-1912.

[5] MatanO, Burges JC, LeCun Y, et al. Multi-digit recognition using a space displacement neural network[C]∥Advances in Neural Information Processing Systems, November 30-December 3, 1992, Denver, Colorado, USA. San Francisco: Margan Kaufmann, 1992: 488- 495.

[6] Hochuli A G, Oliveira L S, Britto A S. Jr, et al. Handwritten digit segmentation: is it still necessary?[J]. Pattern Recognition, 2018, 78: 1-11.

[7] HeK, GkioxariG, DollárP, et al. Mask R-CNN[C]∥Proceedings of the IEEE International Conference on Computer Vision, October 22-29, 2017, Venice, Italy. New York: IEEE, 2017: 2961- 2969.

[8] 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, 2017, 39(6): 1137-1149.

[9] 陶志勇, 王浩童, 王藜谚. 一种主动鉴别未知类别指静脉的识别系统[J]. 激光与光电子学进展, 2018, 55(12): 121002.

    Tao Z Y, Wang H T, Wang L Y. An identification system for actively identifying unknown finger veins[J]. Laser & Optoelectronics Progress, 2018, 55(12): 121002.

[10] 李大军, 何维龙, 郭丙轩, 等. 基于Mask-RCNN的建筑物目标检测算法[J]. 测绘科学, 2019, 44(10): 172-180.

    Li D J, He W L, Guo B X, et al. Building target detection algorithm based on Mask-RCNN[J]. Science of Surveying and Mapping, 2019, 44(10): 172-180.

[11] LongJ, ShelhamerE, DarrellT. Fully convolutional networks for semantic segmentation[C]∥2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 7-12, 2015, Boston, MA, USA. New York: IEEE, 2015: 3431- 3440.

[12] 任之俊, 蔺素珍, 李大威, 等. 基于改进特征金字塔的Mask R-CNN目标检测方法[J]. 激光与光电子学进展, 2019, 56(4): 041512.

    Ren Z J, Lin S Z, Li D W, et al. Mask R-CNN object detection method based on improved feature pyramid[J]. Laser & Optoelectronics Progress, 2019, 56(4): 041512.

[13] 黄伟, 曹宇剑, 徐国明. 基于Faster R-CNN模型的低空平台偏振高光谱目标检测[J]. 红外技术, 2019, 41(7): 600-606.

    Huang W, Cao Y J, Xu G M. Polarized hyperspectral object detection with Faster R-CNN for low-altitude platforms[J]. Infrared Technology, 2019, 41(7): 600-606.

[14] GirshickR, DonahueJ, DarrellT, 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, 2014: 580- 587.

[15] 王森, 杨克俭. 基于双线性插值的图像缩放算法的研究与实现[J]. 自动化技术与应用, 2008, 27(7): 44-45, 35.

    Wang S, Yang K J. An image scaling algorithm based on bilinear interpolation with VC++[J]. Techniques of Automation and Applications, 2008, 27(7): 44-45, 35.

[16] 丁鑫. 基于图像识别的试卷成绩复核系统关键技术研究[D]. 阜新: 辽宁工程技术大学, 2019: 1- 75.

    DingX. Research on key technology of examination paper score review system based on image recognition[D]. Fuxin: Liaoning Technical University, 2019: 1- 75.

[17] 欧攀, 路奎, 张正, 等. 基于Mask RCNN的目标识别与空间定位[J]. 计算机测量与控制, 2019, 27(6): 172-176.

    Ou P, Lu K, Zhang Z, et al. Target recognition and spatial location based on Mask RCNN[J]. Computer Measurement & Control, 2019, 27(6): 172-176.

[18] 张祥甫, 刘健, 石章松, 等. 基于深度学习的语义分割问题研究综述[J]. 激光与光电子学进展, 2019, 56(15): 150003.

    Zhang X F, Liu J, Shi Z S, et al. Review of deep learning-based semantic segmentation[J]. Laser & Optoelectronics Progress, 2019, 56(15): 150003.

[19] 石杰, 周亚丽, 张奇志. 基于改进Mask RCNN和Kinect的服务机器人物品识别系统[J]. 仪器仪表学报, 2019, 40(4): 216-228.

    Shi J, Zhou Y L, Zhang Q Z. Service robot item recognition system based on improved Mask RCNN and Kinect[J]. Chinese Journal of Scientific Instrument, 2019, 40(4): 216-228.

[20] de S Britto A, Sabourin R, Bortolozzi F, et al. The recognition of handwritten numeral strings using a two-stage HMM-based method[J]. International Journal on Document Analysis and Recognition, 2003, 5(2): 102-117.

[21] Oliveira LS, SabourinR. Support vector machines for handwritten numerical string recognition[C]∥Ninth International Workshop on Frontiers in Handwriting Recognition, October 26-29, 2004, Kokubunji, Tokyo, Japan. New York: IEEE, 2004: 39- 44.

[22] Sadri J, Suen C Y, Bui T D. A genetic framework using contextual knowledge for segmentation and recognition of handwritten numeral strings[J]. Pattern Recognition, 2007, 40(3): 898-919.

[23] Gattal A, Chibani Y, Hadjadji B. Segmentation and recognition system for unknown-length handwritten digit strings[J]. Pattern Analysis and Applications, 2017, 20(2): 307-323.