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Received:
2019-05-27
Online:
2020-02-13
Published:
2020-02-13
CLC Number:
WANG Wen, ZHOU Chen-yi, XU Yi-bai, LU Shan, ZHOU Meng-lan. A Multi-scale Feature Fusion Meter Box Rust Spot Detection Algorithm Using Cascaded RPN[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2020.01.022.
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URL: http://www.c-a-m.org.cn/EN/10.3969/j.issn.1006-2475.2020.01.022
[1] LOWE D G. Object recognition from local scale-invariant features[C]// Proceedings of the 7th IEEE International Conference on Computer Vision. 1999,2:1150-1157. [2] JOACHIMS T. Making Large-scale SVM Learning Practical[R]. University of Dortmund, 1998. [3] 〖JP+2〗CANNY J. A computational approach to edge detection[M]// Readings in Computer Vision. Morgan Kaufmann, 1987:184-203. [4] REN S Q, HE K M, GIRSHICK R, et al. Faster R-CNN: 〖JP+1〗Towards real-time object detection with region proposal networks[C]// Proceedings of the 28th International Conference on Neural Information Processing Systems. 2015:91-99. [5] SHEN H K, CHEN P H, CHANG L M. Automated steel bridge coating rust defect recognition method based on color and texture feature[J]. Automation in Construction, 2013,31:338-356. [6] 姚明海,陈志浩. 基于深度主动学习的磁片表面缺陷检测[J]. 计算机测量与控制, 2018,26(9):29-33. [7] LI P Z, LIN L X, CHEN Y. A SROD algorithm based accurate detection method for surface rust spots in ocean ship[J]. Journal of Coastal Research, 2018,83:921-926. [8] LIAO K W, LEE Y T. Detection of rust defects on steel bridge coatings via digital image recognition[J]. Automation in Construction, 2016,71:294-306. [9] 安宗权,王匀. 一种非线性扩散与图像差分的金属表面缺陷检测方法[J]. 表面技术, 2018,47(6):277-283. [10]ZHANG N, DONAHUE J, GIRSHICK R, et al. Part-based R-CNNs for fine-grained category detection[C]// Proceedings of the 2014 European Conference on Computer Vision. 2014:834-849. [11]LIN T Y, ROYCHOWDHURY A, MAJI S. Bilinear CNN models for fine-grained visual recognition[C]// Proceedings of the 2015 IEEE International Conference on Computer Vision. 2015:1449-1457. [12]BRANSON S, VAN HORN G, BELONGIE S, et al. Bird Species Categorization Using Pose Normalized Deep Convolutional Nets[DB/OL]. (2014-06-11)[2019-05-06]. https://arxiv.org/pdf/1406.2952.pdf. [13]〖JP+1〗WANG Y M, MORARIU V I, DAVIS L S. Learning a discriminative filter bank within a CNN for fine-grained recognition[C]// Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition. 2018:4148-4157. [14]HE K M, ZHANG X Y, REN S Q, et al. Deep residual learning for image recognition[C]// Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition. 2016:770-778. [15]LIN T Y, DOLLAR P, GIRSHICK R, et al. Feature pyramid networks for object detection[C]// Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition. 2017:936-944. [16]〖JP+2〗YANG B, YAN J J, LEI Z, et al. CRAFT objects from images[C]// Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition. 2016:6043-6051. [17]〖JP+1〗LIN G S, MILAN A, SHEN C H, et al. RefineNet: Multi-path refinement networks for high-resolution semantic segmentation[C]// Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition. 2017:5168-5177. [18]JAIN S D, XIONG B, GRAUMAN K.FusionSeg: Learning to combine motion and appearance for fully automatic segmentation of generic objects in videos[C]// Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition. 2017:2117-2126. [19]HE K M, ZHANG X Y, REN S Q, et al. Spatial pyramid pooling in deep convolutional networks for visual recognition[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015,37(9):1904-1916. [20]ABADI M, BARHAM P, CHEN J M, et al. TensorFlow: A system for large-scale machine learning[C]// Proceedings of the 12th USENIX Conference on Operating Systems Design and Implementation. 2016:265-283. [21]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. 2012:1097-1105. [22]〖JP2〗REDMON J, FARHADI A. YOLO9000: Better, faster, stronger[C]// Proceedings of 2017 IEEE Conference on Computer Vision and Pattern Recognition. 2017:6517-6525. [23]WANG R J, LI X, LING C X. Pelee: A real-time object detection system on mobile devices[C]// Proceedings of the 31st International Conference on Neural Information Processing Systems. 2018:1963-1972. |
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