Fetching the paper…
Reading the bibliography…
Binary Neural Networks (BNNs) show promising progress in reducing computational and memory costs but suffer from substantial accuracy degradation compared to their real-valued counterparts on large-scale datasets, e.g., ImageNet.
Imagenet: A large-scale hierarchical image database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
Earlier work this paper cites.
The pascal visual object classes (voc) challenge
M. Everingham, L. Gool, C. K. Williams, J. Winn, and A. Zisserman · 2010
Earlier work this paper cites.
Cifar-10
A. Krizhevsky, V. Nair, and G. Hinton · 2010
Earlier work this paper cites.
Estimating or propagating gradients through stochastic neurons for conditional computation
Y. Bengio, N. Léonard, and A. C. Courville · 2013
Earlier work this paper cites.
Rich feature hierarchies for accurate object detection and semantic segmentation
R. Girshick, J. Donahue, T. Darrell, and J. Malik · 2014
Earlier work this paper cites.
Deep features for text spotting
M. Jaderberg, A. Vedaldi, and A. Zisserman · 2014
Earlier work this paper cites.
Binaryconnect: Training deep neural networks with binary weights during propagations
M. Courbariaux, Y. Bengio, and J.-P. David · 2015
Earlier work this paper cites.
Batch normalization: Accelerating deep network training by reducing internal covariate shift
S. Ioffe and C. Szegedy · 2015
Earlier work this paper cites.
Adam: A method for stochastic optimization
D. P. Kingma and J. Ba · 2015
Earlier work this paper cites.
Faster r-cnn: Towards real-time object detection with region proposal networks
S. Ren, K. He, R. Girshick, and J. Sun · 2015
Earlier work this paper cites.
Going deeper with convolutions
C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, A. Rabinovich, and Others · 2015
Earlier work this paper cites.
Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding
S. Han, H. Mao, and W. J. Dally · 2016
Cited alongside, same era.
Binarized neural networks
I. Hubara, M. Courbariaux, D. Soudry, R. El-Yaniv, and Y. Bengio · 2016
Cited alongside, same era.
Squeezenet: Alexnet-level accuracy with 50x fewer parameters and 0.5 mb model size
F. N. Iandola, S. Han, M. W. Moskewicz, K. Ashraf, W. J. Dally, and K. Keutzer · 2016
Cited alongside, same era.
SSD: single shot multibox detector
W. Liu, D. Anguelov, D. Erhan, C. Szegedy, S. E. Reed, C. Fu, and A. C. Berg · 2016
Cited alongside, same era.
Xnor-net: Imagenet classification using binary convolutional neural networks
M. Rastegari, V. Ordonez, J. Redmon, and A. Farhadi · 2016
Cited alongside, same era.
You only look once: Unified, real-time object detection
Towards accurate binary convolutional neural network
X. Lin, C. Zhao, and W. Pan · 2017
Later among the works it cites.
How to Train a Compact Binary Neural Network with High Accuracy
W. Tang, G. Hua, and L. Wang · 2017
Later among the works it cites.
Bmxnet: An open-source binary neural network implementation based on mxnet
H. Yang, M. Fritzsche, C. Bartz, and C. Meinel · 2017
Later among the works it cites.
Adaptive Quantization for Deep Neural Network
Y. Zhou, S.-M. Moosavi-Dezfooli, N.-M. Cheung, and P. Frossard · 2017
Later among the works it cites.
Learning to train a binary neural network
J. Bethge, H. Yang, C. Bartz, and C. Meinel · 2018
Later among the works it cites.
Syq: Learning symmetric quantization for efficient deep neural networks
J. Faraone, N. Fraser, M. Blott, and P. H. Leong · 2018
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
J. Redmon, S. K. Divvala, R. B. Girshick, and A. Farhadi · 2016
Cited alongside, same era.
Dorefa-net: Training low bitwidth convolutional neural networks with low bitwidth gradients
S. Zhou, Y. Wu, Z. Ni, X. Zhou, H. Wen, and Y. Zou · 2016
Cited alongside, same era.
C. Zhu, S. Han, H. Mao, and W. J. Dally · 2016
Cited alongside, same era.
Mobilenets: Efficient convolutional neural networks for mobile vision applications
A. G. Howard, M. Zhu, B. Chen, D. Kalenichenko, W. Wang, T. Weyand, M. Andreetto, and H. Adam · 2017
Cited alongside, same era.
Densely connected convolutional networks
G. Huang, Z. Liu, K. Q. Weinberger, and L. van der Maaten · 2017
Cited alongside, same era.
Performance guaranteed network acceleration via high-order residual quantization
Z. Li, B. Ni, W. Zhang, X. Yang, and W. Gao · 2017
Cited alongside, same era.
Later among the works it cites.
Bag of tricks for image classification with convolutional neural networks
T. He, Z. Zhang, H. Zhang, Z. Zhang, J. Xie, and M. Li · 2018
Later among the works it cites.
Bi-real net: Binarizing deep network towards real-network performance
Z. Liu, W. Luo, B. Wu, X. Yang, W. Liu, and K. Cheng · 2018
Later among the works it cites.
Bi-real net: Enhancing the performance of 1-bit cnns with improved representational capability and advanced training algorithm
Z. Liu, B. Wu, W. Luo, X. Yang, W. Liu, and K.-T. Cheng · 2018
Later among the works it cites.
Tbn: Convolutional neural network with ternary inputs and binary weights
D. Wan, F. Shen, L. Liu, F. Zhu, J. Qin, L. Shao, and H. Tao Shen · 2018
Later among the works it cites.
Shufflenet: An extremely efficient convolutional neural network for mobile devices
X. Zhang, X. Zhou, M. Lin, and J. Sun · 2018
Later among the works it cites.