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In object detection, reducing computational cost is as important as improving accuracy for most practical usages.
Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
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Compression of deep convolutional neural networks for fast and low power mobile applications
Yong-Deok Kim, Eunhyeok Park, Sungjoo Yoo, Taelim Choi, Lu Yang, and Dongjun Shin · 2015
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Training cnns with low-rank filters for efficient image classification
Yani Ioannou, Duncan Robertson, Jamie Shotton, Roberto Cipolla, and Antonio Criminisi · 2015
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Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
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Striving for simplicity: The all convolutional net
J Springenberg, Alexey Dosovitskiy, Thomas Brox, and M Riedmiller · 2015
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Faster R-CNN: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
Cited alongside, same era.
Hypercolumns for object segmentation and fine-grained localization
Bharath Hariharan, Pablo Arbeláez, Ross Girshick, and Jitendra Malik · 2015
Cited alongside, same era.
Object detection via a multi-region & semantic segmentation-aware CNN model
Spyros Gidaris and Nikos Komodakis · 2015
Cited alongside, same era.
Fast R-CNN
Ross Girshick · 2015
Cited alongside, same era.
SSD: Single shot multibox detector
Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, and Alexander C. Berg · 2015
Cited alongside, same era.
Squeezenet: Alexnet-level accuracy with 50x fewer parameters and¡ 1mb model size
Understanding and improving convolutional neural networks via concatenated rectified linear units
Wenling Shang, Kihyuk Sohn, Diogo Almeida, and Honglak Lee · 2016
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HyperNet: Towards accurate region proposal generation and joint object detection
Tao Kong, Anbang Yao, Yurong Chen, and Fuchun Sun · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Identity mappings in deep residual networks
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Inside-outside net: Detecting objects in context with skip pooling and recurrent neural networks
Sean Bell, C. Lawrence Zitnick, Kavita Bala, and Ross Girshick · 2016
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Forrest N Iandola, Matthew W Moskewicz, Khalid Ashraf, Song Han, William J Dally, and Kurt Keutzer · 2016
Cited alongside, same era.
Jifeng Dai, Yi Li, Kaiming He, and Jian Sun · 2016
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