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Traditionally, an object detector is applied to every part of the scene of interest, and its accuracy and computational cost increases with higher resolution images.
Q-learning
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Sliding-windows for rapid object class localization: A parallel technique
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Active object localization with deep reinforcement learning
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An active search strategy for efficient object class detection
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A convolutional neural network cascade for face detection
H. Li, Z. Lin, X. Shen, J. Brandt, and G. Hua · 2015
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Faster r-cnn: Towards real-time object detection with region proposal networks
S. Ren, K. He, R. Girshick, and J. Sun · 2015
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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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Fully-convolutional siamese networks for object tracking
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Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
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Dynamic Zoom-in Network for Fast Object Detection in Large Images
M. Gao, R. Yu, A. Li, V. I. Morariu, and L. S. Davis · 2018
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ClusterNet: Detecting Small Objects in Large Scenes by Exploiting Spatio-Temporal Information
R. LaLonde, D. Zhang, and M. Shah · 2018
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Deep Residual Learning for Image Recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
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What makes imagenet good for transfer learning?
M. Huh, P. Agrawal, and A. A. Efros · 2016
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Tree-Structured Reinforcement Learning for Sequential Object Localization
Z. Jie, X. Liang, J. Feng, X. Jin, W. Lu, and S. Yan · 2016
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SSD: Single Shot MultiBox Detector
W. Liu, D. Anguelov, D. Erhan, C. Szegedy, S. Reed, C.-Y. Fu, and A. C. Berg · 2016
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Adaptive object detection using adjacency and zoom prediction
Y. Lu, T. Javidi, and S. Lazebnik · 2016
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Reinforcement learning for visual object detection
S. Mathe, A. Pirinen, and C. Sminchisescu · 2016
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D. Lam, R. Kuzma, K. McGee, S. Dooley, M. Laielli, M. Klaric, Y. Bulatov, and B. McCord · 2018
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Autofocus: Efficient multi-scale inference
M. Najibi, B. Singh, and L. S. Davis · 2018
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Deep reinforcement learning of region proposal networks for object detection
A. Pirinen and C. Sminchisescu · 2018
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YOLOv3: An Incremental Improvement
J. Redmon and A. Farhadi · 2018
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Learning to interpret satellite images using wikipedia
E. Sheehan, B. Uzkent, C. Meng, Z. Tang, M. Burke, D. Lobell, and S. Ermon · 2018
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Reinforcement learning: An introduction
R. S. Sutton and A. G. Barto · 2018
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Tracking in aerial hyperspectral videos using deep kernelized correlation filters
B. Uzkent, A. Rangnekar, and M. J. Hoffman · 2018
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Enkcf: Ensemble of kernelized correlation filters for high-speed object tracking
B. Uzkent and Y. Seo · 2018
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Blockdrop: Dynamic inference paths in residual networks
Z. Wu, T. Nagarajan, A. Kumar, S. Rennie, L. S. Davis, K. Grauman, and R. Feris · 2018
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Using pre-training can improve model robustness and uncertainty
D. Hendrycks, K. Lee, and M. Mazeika · 2019
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Reduced focal loss: 1st place solution to xview object detection in satellite imagery
N. Sergievskiy and A. Ponamarev · 2019
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Predicting economic development using geolocated wikipedia articles
E. Sheehan, C. Meng, M. Tan, B. Uzkent, N. Jean, M. Burke, D. Lobell, and S. Ermon · 2019
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Learning to interpret satellite images in global scale using wikipedia
B. Uzkent, E. Sheehan, C. Meng, Z. Tang, M. Burke, D. Lobell, and S. Ermon · 2019
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