|
[1] Alex Krizhevsky, Ilya Sutskever, and Geoffrey E. Hinton. 2012. ImageNet Classification with Deep Convolutional Neural Networks. In Proceedings of International Conference on Neural Information Processing Systems. 1097–1105.
[2] Jonathan Long, Evan Shelhamer, and Trevor Darrell. 2015. Fully Convolutional Networks for Semantic Segmentation. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.
[3] Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun. 2017. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks. IEEE Transactions on Pattern Analysis and Machine Intelligence 39, 6 (2017), 1137–1149.
[4] Matthew D. Zeiler and Rob Fergus. 2014. Visualizing and Understanding Convolutional Networks. In Proceedings of European Conference on Computer Vision.
[5] Erzhu Li, Junshi Xia, Peijun Du, Cong Lin, and Alim Samat. 2017. Integrating Multilayer Features of Convolutional Neural Networks for Remote Sensing Scene Classification. IEEE Transactions on Geoscience and Remote Sensing 55, 10 (2017), 5653–5665.
[6] Florent Perronnin, Jorge Sanchez, and Thomas Mensink. 2010. Improving the Fisher Kernel for Large-Scale Image Classification. In Proceedings of European Conference on Computer Vision.
[7] Xiaodong Yang, Pavlo Molchanov, and Jan Kautz. 2016. Multilayer and Multimodal Fusion of Deep Neural Networks for Classification. In Proceedings of ACM Multimedia Conference. 978–987.
[8] John R. Koza. 1992. Genetic Programming: On the Programming of Computers by Means of Natural Selection. MIT Press.
[9] John H. Holland. 1992. Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence. MIT Press.
[10] Yangqing Jia, Evan Shelhamer, Jeff Donahue, Sergey Karayev, Jonathan Long, Ross Girshick, Sergio Guadarrama, and Trevor Darrell. 2014. Caffe: Convolutional Architecture for Fast Feature Embedding. In Proceedings of ACM International Conference on Multimedia. 675–678.
[11] Ken Chatfield, Karen Simonyan, Andrea Vedaldi, and Andrew Zisserman. 2014. Return of the Devil in the Details: Delving Deep into Convolutional Networks. In Proceedings of British Machine Vision Conference.
[12] Karen Simonyan and Andrew Zisserman. 2015. Very Deep Convolutional Networks for Large-Scale Image Recognition. In Proceedings of International Conference on Learning Representation.
[13] Yukhe Lavinia, Holly H. Vo, and Abhishek Verma. 2016. Fusion Based Deep CNN for Improved Large-Scale Image Action Recognition. In Proceedings of IEEE International Symposium on Multimedia. 609-614.
[14] Songfan Yang and Deva Ramanan. 2015. Multi-scale Recognition with DAG-CNNs. In Proceedings of IEEE International Conference on Computer Vision.
[15] Bharath Hariharan, Pablo Arbelaez, Ross Girshick, and Jitendra Malik. 2015. Hypercolumns for Object Segmentation and Fine-grained Localization. In Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition.
[16] Alexey Dosovitskiy, Philipp Fischer, Eddy Ilg, Philip Hausser, Caner Hazirbas, Vladimir Golkov, Patrick van der Smagt, Daniel Cremers, and Thomas Brox. 2015. FlowNet: Learning Optical Flow with Convolutional Networks. In Proceedings of IEEE International Conference on Computer Vision.
[17] Ling Shao, Li Liu, and Xuelong Li. 2014. Feature Learning for Image Classification Via Multiobjective Genetic Programming. IEEE Transactions on Neural Networks and Learning Systems 25, 7 (2014), 1359–1371.
[18] Yuyu Liang, Mengjie Zhang, and Will N. Browne. 2016. Figure-ground Image Segmentation Using Genetic Programming and Feature Selection. In Proceedings of IEEE Congress on Evolutionary Computation.
[19] Harith Al-Sahaf, Ausama Al-Sahaf, Bing Xue, Mark Johnston, and Mengjie Zhang. 2017. Automatically Evolving Rotation-Invariant Texture Image Descriptors by Genetic Programming. IEEE Transactions on Evolutionary Computation 21, 1 (2017), 83–101.
[20] Masanori Suganuma, Shinichi Shirakawa, and Tomoharu Nagao. 2017. A Genetic Programming Approach to Designing Convolutional Neural Network Architectures. In Proceedings of the Genetic and Evolutionary Computation Conference. 497–504.
[21] Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, Andrew Rabinovich. 2015. Going Deeper with Convolutions. In Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition.
[22] Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. 2016. Deep Residual Learning for Image Recognition. In Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition. 770-778.
[23] Li Fei-Fei, Rob Fergus, and Pietro Perona. 2004. Learning Generative Visual Models from Few Training Examples: An Incremental Bayesian Approach Tested on 101 Object Categories. In Proceedings of CVPR Workshop of Generative Model Based Vision.
[24] Gregory Griffin, Alex Holub, and Pietro Perona. 2007. Caltech-256 Object Category Dataset. Technical Report. California Institute of Technology.
[25] Bangpeng Yao, Xiaoye Jiang, Aditya Khosla, Andy Lai Lin, Leonidas Guibas, and Li Fei-Fei. 2011. Human Action Recognition by Learning Bases of Action Attributes and Parts. In Proceedings of IEEE International Conference on Computer Vision.
[26] Navneet Dadal and Bill Triggs. 2005. Histograms of Oriented Gradients for Human Detection. In Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition. 886–893.
[27] David Lowe. 2004. Distinctive Image Features from Scale-Invariant Keypoints. International Journal of Computer Vision 60, 2 (2004), 91–110.
[28] Timo Ahoene, Abdenour Hadid, and Matti Pietikainen. 2004. Face Recognition with Local Binary Patterns. In Proceedings of European Conference on Computer Vision. 469–481.
[29] David Martin, Charless Fowlkes, Doron Tal, and Jitendra Malik. 2001. A Database of Human Segmented Natural Images and its Application to Evaluating Segmentation Algorithms and Measuring Ecological Statistics. In Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition. 416–423.
[30] Jianxin Wu and Jim Rehg. 2011. CENTRIST: A Visual Descriptor for Scene Categorization. IEEE Transactions on Pattern Analysis and Machine Intelligence 33, 8 (2011), 1489–1501.
[31] Gao Huang, Zhuang Liu, Laurens van der Maaten, and Kilian Q. Weinberger. 2017. Densely Connected Convolutional Networks. In Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition.
|