Hierarchical Image Object Search Based on Deep Reinforcement Learning
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References
- Sutton R S, Barto A G. Reinforcement learning: An introduction[M]. MIT press, 2018.
- Gagniuc P A. Markov chains: from theory to implementation and experimentation[M]. John Wiley & Sons, 2017.
- Hu Y, Xie X, Ma W Y, et al. Salient region detection using weighted feature maps based on the human visual attention model[C]//Pacific-Rim Conference on Multimedia. Springer, Berlin, Heidelberg, 2004: 993-1000.
- Ren S, He K, Girshick R, et al. Faster r-cnn: Towards real-time object detection with region proposal networks[C]//Advances in neural information processing systems. 2015: 91-99.
- LeCun Y, Bottou L, Bengio Y, et al. Gradient-based learning applied to document recognition[J]. Proceedings of the IEEE, 1998, 86(11): 2278-2324.
- Dalal N, Triggs B. Histograms of oriented gradients for human detection[C]//2005 IEEE computer society conference on computer vision and pattern recognition (CVPR'05). IEEE, 2005, 1: 886-893.
- Boser B E, Guyon I M, Vapnik V N. A training algorithm for optimal margin classifiers[C]//Proceedings of the fifth annual workshop on Computational learning theory. 1992: 144-152.
- Papandreou G, Kokkinos I, Savalle P A. Modeling local and global deformations in deep learning: Epitomic convolution, multiple instance learning, and sliding window detection[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2015: 390-399.
- Carreira J, Sminchisescu C. CPMC: Automatic object segmentation using constrained parametric min-cuts[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 34(7): 1312-1328.
- Uijlings J R R, Van De Sande K E A, Gevers T, et al. Selective search for object recognition[J]. International journal of computer vision, 2013, 104(2): 154-171.
- Pont-Tuset J, Arbelaez P, Barron J T, et al. Multiscale combinatorial grouping for image segmentation and object proposal generation[J]. IEEE transactions on pattern analysis and machine intelligence, 2016, 39(1): 128-140.
- Silver D, Huang A, Maddison C J, et al. Mastering the game of Go with deep neural networks and tree search[J]. nature, 2016, 529(7587): 484-489.
- Caicedo J C, Lazebnik S. Active object localization with deep reinforcement learning[C]//Proceedings of the IEEE international conference on computer vision. 2015: 2488-2496.
- Mathe S, Pirinen A, Sminchisescu C. Reinforcement learning for visual object detection[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2016: 2894-2902.
- Watkins C J C H, Dayan P. Q-learning[J]. Machine learning, 1992, 8(3-4): 279-292.
- Mnih V, Kavukcuoglu K, Silver D, et al. Playing atari with deep reinforcement learning[J]. arXiv preprint arXiv: 1312.5602, 2013.
DOI: https://doi.org/10.21307/ijanmc-2020-029 | Journal eISSN: 2470-8038
Language: English
Page range: 65 - 72
Published on: Oct 14, 2020
Published by: Xi’an Technological University
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
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© 2020 Wei Zhang, Hongge Yao, Yuxing Tan, published by Xi’an Technological University
This work is licensed under the Creative Commons Attribution 4.0 License.