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The objective of this paper is the effective transfer of the Convolutional Neural Network (CNN) feature in image search and classification.
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Discriminative color descriptors
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Neural codes for image retrieval
A. Babenko, A. Slesarev, A. Chigorin, and V. Lempitsky · 2014
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F. Zhu, Z. Jiang, and L. Shao · 2014
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Q. Liu and C. Liu · 2015
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Hypercolumns for object segmentation and fine-grained localization
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Spatial pyramid pooling in deep convolutional networks for visual recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2014
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Fully convolutional networks for semantic segmentation
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Generalized max pooling
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Deep epitomic convolutional neural networks
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Deep convolutional features for image based retrieval and scene categorization
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Fine-grained visual categorization via multi-stage metric learning
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ImageNet Large Scale Visual Recognition Challenge
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, A. C. Berg, and L. Fei-Fei · 2015
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A baseline for visual instance retrieval with deep convolutional networks
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The application of two-level attention models in deep convolutional neural network for fine-grained image classification
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Image classification and retrieval are one
L. Xie, Q. Tian, R. Hong, and B. Zhang · 2015
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A discriminative cnn video representation for event detection
Z. Xu, Y. Yang, and A. G. Hauptmann · 2015
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Multi-scale pyramid pooling for deep convolutional representation
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Query-adaptive late fusion for image search and person re-identification
L. Zheng, S. Wang, L. Tian, F. He, Z. Liu, and Q. Tian · 2015
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