14.5.10.8.1 Binary Neural Networks, BNN

Liu, C.L.[Chun-Lei], Ding, W.R.[Wen-Rui], Wang, X.D.[Xiao-Di], Zhang, B.C.[Bao-Chang],
Hybrid Gabor Convolutional Networks,
PRL(116), 2018, pp. 164-169.
Elsevier DOI 1812
Hybrid Gabor Convolutional Networks, Convolutional neural network, Binary networks, Deep learning BibRef

Jiang, Y.S.[Yan-Shu], Zhao, T.L.[Tian-Li], He, X.Y.[Xiang-Yu], Leng, C.[Cong], Cheng, J.[Jian],
BitStream: An efficient framework for inference of binary neural networks on CPUs,
PRL(125), 2019, pp. 303-309.
Elsevier DOI 1909
Convolutional neural networks, Binary neural networks, Image classification BibRef

Ignatov, D.[Dmitry], Ignatov, A.[Andrey],
Controlling information capacity of binary neural network,
PRL(138), 2020, pp. 276-281.
Elsevier DOI 2010
Deep learning, Binary neural network, Information theory, Shannon entropy BibRef

Zhou, X.C.[Xi-Chuan], Ding, R.[Rui], Liu, H.J.[Hai-Jun],
LC-BiDet: Laterally Connected Binary Detector with Efficient Image Processing,
SPLetters(29), 2022, pp. 1262-1266.
IEEE DOI 2206
Detectors, Convolution, Object detection, Training, Feature extraction, Convolutional neural networks, regularization term BibRef

Liu, C.L.[Chun-Lei], Ding, W.R.[Wen-Rui], Chen, P.[Peng], Zhuang, B.[Bohan], Wang, Y.F.[Yu-Feng], Zhao, Y.[Yang], Zhang, B.C.[Bao-Chang], Han, Y.[Yuqi],
RB-Net: Training Highly Accurate and Efficient Binary Neural Networks With Reshaped Point-Wise Convolution and Balanced Activation,
CirSysVideo(32), No. 9, September 2022, pp. 6414-6424.
IEEE DOI 2209
Convolution, Neural networks, Standards, Kernel, Training, Computational efficiency, Spatial databases, object classification BibRef

Wang, Q.[Qi], Guo, N.[Nianhui], Xiong, Z.[Zhitong], Yin, Z.[Zeping], Li, X.L.[Xue-Long],
Gradient Matters: Designing Binarized Neural Networks via Enhanced Information-Flow,
PAMI(44), No. 11, November 2022, pp. 7551-7562.
IEEE DOI 2210
Convolution, Training, Neural networks, Optimization, Robustness, Kernel, Feature extraction, Neural network accelerating, gradient approximation BibRef

Qin, H.T.[Hao-Tong], Zhang, X.G.[Xiang-Guo], Gong, R.H.[Rui-Hao], Ding, Y.[Yifu], Xu, Y.[Yi], Liu, X.L.[Xiang-Long],
Distribution-Sensitive Information Retention for Accurate Binary Neural Network,
IJCV(131), No. 1, January 2023, pp. 26-47.
Springer DOI 2301
BibRef

Qin, H.T.[Hao-Tong], Gong, R.H.[Rui-Hao], Liu, X.L.[Xiang-Long], Shen, M., Wei, Z., Yu, F., Song, J.,
Forward and Backward Information Retention for Accurate Binary Neural Networks,
CVPR20(2247-2256)
IEEE DOI 2008
Quantization (signal), Training, Backpropagation, Propagation losses, Biological neural networks, Information entropy BibRef

Chien, J.T.[Jen-Tzung], Chang, S.T.[Su-Ting],
Bayesian asymmetric quantized neural networks,
PR(139), 2023, pp. 109463.
Elsevier DOI 2304
Quantized neural network, Model compression, Binary neural network, Bayesian asymmetric quantization BibRef

Zhao, Z.[Zhi], Xu, K.[Ke], Ma, Y.X.[Yan-Xin], Wan, J.W.[Jian-Wei],
A gradient optimization and manifold preserving based binary neural network for point cloud,
PR(139), 2023, pp. 109445.
Elsevier DOI 2304
Binarization, Gradient optimization, Manifold, Point cloud BibRef

Lin, M.B.[Ming-Bao], Ji, R.R.[Rong-Rong], Xu, Z.[Zihan], Zhang, B.C.[Bao-Chang], Chao, F.[Fei], Lin, C.W.[Chia-Wen], Shao, L.[Ling],
SiMaN: Sign-to-Magnitude Network Binarization,
PAMI(45), No. 5, May 2023, pp. 6277-6288.
IEEE DOI 2304
Quantization (signal), Optimization, Training, Neural networks, Entropy, Computational modeling, Laplace equations, weight magnitude BibRef

Lin, Y.[Yuhan], Niu, L.F.[Ling-Feng], Xiao, Y.[Yang], Zhou, R.Z.[Rui-Zhi],
Diluted binary neural network,
PR(140), 2023, pp. 109556.
Elsevier DOI 2305
Model compression, Network quantization, Binary neural network, Ternary neural network, Sparse regularization BibRef

Ahn, D.[Daehyun], Kim, H.[Hyungjun], Kim, T.[Taesu], Park, E.[Eunhyeok], Kim, J.J.[Jae-Joon],
Searching for Robust Binary Neural Networks via Bimodal Parameter Perturbation,
WACV23(2409-2418)
IEEE DOI 2302
Gradient methods, Convolution, Perturbation methods, Neural networks, Search problems, Stability analysis, visual reasoning BibRef

Falkena, S.[Sieger], Jamali-Rad, H.[Hadi], van Gemert, J.[Jan],
LAB: Learnable Activation Binarizer for Binary Neural Networks,
WACV23(6414-6423)
IEEE DOI 2302
Deep learning, Limiting, Costs, Neural networks, Delays, Applications: Embedded sensing/real-time techniques, Smartphones/end user devices BibRef

Xu, S.[Sheng], Li, Y.J.[Yan-Jing], Wang, T.C.[Tian-Cheng], Ma, T.[Teli], Zhang, B.C.[Bao-Chang], Gao, P.[Peng], Qiao, Y.[Yu], Lü, J.[Jinhu], Guo, G.D.[Guo-Dong],
Recurrent Bilinear Optimization for Binary Neural Networks,
ECCV22(XXIV:19-35).
Springer DOI 2211
BibRef

Tu, Z.J.[Zhi-Jun], Chen, X.H.[Xing-Hao], Ren, P.J.[Peng-Ju], Wang, Y.H.[Yun-He],
AdaBin: Improving Binary Neural Networks with Adaptive Binary Sets,
ECCV22(XI:379-395).
Springer DOI 2211
BibRef

Xing, X.R.[Xing-Run], Li, Y.G.[Yang-Guang], Li, W.[Wei], Ding, W.R.[Wen-Rui], Jiang, Y.L.[Ya-Long], Wang, Y.F.[Yu-Feng], Shao, J.[Jing], Liu, C.L.[Chun-Lei], Liu, X.L.[Xiang-Long],
Towards Accurate Binary Neural Networks via Modeling Contextual Dependencies,
ECCV22(XI:536-552).
Springer DOI 2211
BibRef

Shang, Y.Z.[Yu-Zhang], Xu, D.[Dan], Duan, B.[Bin], Zong, Z.L.[Zi-Liang], Nie, L.Q.[Li-Qiang], Yan, Y.[Yan],
Lipschitz Continuity Retained Binary Neural Network,
ECCV22(XI:603-619).
Springer DOI 2211
BibRef

Aouad, T.[Theodore], Talbot, H.[Hugues],
Binary Morphological Neural Network,
ICIP22(3276-3280)
IEEE DOI 2211
Measurement, Convolutional codes, Neurons, Pipelines, Morphology, Information filters, Convolutional neural networks, image processing BibRef

Zhang, Y.C.[Yi-Chi], Zhang, Z.R.[Zhi-Ru], Lew, L.[Lukasz],
PokeBNN: A Binary Pursuit of Lightweight Accuracy,
CVPR22(12465-12475)
IEEE DOI 2210
Measurement, Deep learning, Costs, Convolution, Neural networks, Hardware, Machine learning BibRef

Le, H.[Huu], Høier, R.K.[Rasmus Kjær], Lin, C.T.[Che-Tsung], Zach, C.[Christopher],
AdaSTE: An Adaptive Straight-Through Estimator to Train Binary Neural Networks,
CVPR22(460-469)
IEEE DOI 2210
Training, Deep learning, Autonomous systems, Neural networks, Software algorithms, Software, Optimization methods, Machine learning BibRef

Kim, D.[Dahyun], Choi, J.H.[Jong-Hyun],
Unsupervised Representation Learning for Binary Networks by Joint Classifier Learning,
CVPR22(9737-9746)
IEEE DOI 2210
Representation learning, Training, Codes, Surveillance, Self-supervised learning, Vision sensors, Feature extraction, Self- semi- meta- Efficient learning and inferences BibRef

Sasdelli, M.[Michele], Chin, T.J.[Tat-Jun],
Quantum Annealing Formulation for Binary Neural Networks,
DICTA21(1-10)
IEEE DOI 2201
Computers, Training, Deep learning, Annealing, Computational modeling, Neural networks, Writing BibRef

Kim, H.J.[Hyung-Jun], Park, J.[Jihoon], Lee, C.H.[Chang-Hun], Kim, J.J.[Jae-Joon],
Improving Accuracy of Binary Neural Networks using Unbalanced Activation Distribution,
CVPR21(7858-7867)
IEEE DOI 2111
Degradation, Deep learning, Analytical models, Computational modeling, Neural networks, Mobile handsets BibRef

Suarez-Ramirez, C.D.[Cuauhtemoc Daniel], Gonzalez-Mendoza, M.[Miguel], Chang, L.[Leonardo], Ochoa-Ruiz, G.[Gilberto], Duran-Vega, M.A.[Mario Alberto],
A Bop and Beyond: A Second Order Optimizer for Binarized Neural Networks,
LXCV21(1273-1281)
IEEE DOI 2109
Training, Artificial neural networks, Pattern recognition, Optimization BibRef

Redfern, A.J.[Arthur J.], Zhu, L.J.[Li-Jun], Newquist, M.K.[Molly K.],
BCNN: A Binary CNN With All Matrix Ops Quantized To 1 Bit Precision,
BiVision21(4599-4607)
IEEE DOI 2109
Training, Convolution, Neural networks, Memory management, Decoding BibRef

Razani, R.[Ryan], Morin, G.[Grégoire], Sari, E.[Eyyüb], Nia, V.P.[Vahid Partovi],
Adaptive Binary-Ternary Quantization,
BiVision21(4608-4613)
IEEE DOI 2109
Training, Adaptation models, Quantization (signal), Computational modeling, Wearable computers, Neural networks, Speech recognition BibRef

Chen, T.L.[Tian-Long], Zhang, Z.Y.[Zhen-Yu], Ouyang, X.[Xu], Liu, Z.C.[Ze-Chun], Shen, Z.Q.[Zhi-Qiang], Wang, Z.Y.[Zhang-Yang],
'BNN - BN = ?': Training Binary Neural Networks without Batch Normalization,
BiVision21(4614-4624)
IEEE DOI 2109
Training, Neural networks, Standardization, Hardware, Pattern recognition BibRef

Samragh, M.[Mohammad], Hussain, S.[Siam], Zhang, X.[Xinqiao], Huang, K.[Ke], Koushanfar, F.[Farinaz],
On the Application of Binary Neural Networks in Oblivious Inference,
BiVision21(4625-4634)
IEEE DOI 2109
Training, Data analysis, Computational modeling, Face recognition, Neural networks, Data models BibRef

Laydevant, J.[Jérémie], Ernoult, M.[Maxence], Querlioz, D.[Damien], Grollier, J.[Julie],
Training Dynamical Binary Neural Networks with Equilibrium Propagation,
BiVision21(4635-4644)
IEEE DOI 2109
Training, Neuromorphics, Heuristic algorithms, Neurons, Memory management, Hardware, System-on-chip BibRef

Pan, H.Y.[Hong-Yi], Badawi, D.[Diaa], Cetin, A.E.[Ahmet Enis],
Fast Walsh-Hadamard Transform and Smooth-Thresholding Based Binary Layers in Deep Neural Networks,
BiVision21(4645-4654)
IEEE DOI 2109
Deep learning, Tensors, Convolution, Transforms, Computer architecture BibRef

Livochka, A.[Anastasiia], Shekhovtsov, A.[Alexander],
Initialization and Transfer Learning of Stochastic Binary Networks from Real-Valued Ones,
BiVision21(4655-4663)
IEEE DOI 2109
Training, Transfer learning, Neural networks, Stochastic processes, Pattern recognition BibRef

He, X.Y.[Xiang-Yu], Mo, Z.T.[Zi-Tao], Cheng, K.[Ke], Xu, W.X.[Wei-Xiang], Hu, Q.H.[Qing-Hao], Wang, P.S.[Pei-Song], Liu, Q.S.[Qing-Shan], Cheng, J.[Jian],
Proxybnn: Learning Binarized Neural Networks via Proxy Matrices,
ECCV20(III:223-241).
Springer DOI 2012
BibRef

Liu, Z.C.[Ze-Chun], Shen, Z.Q.[Zhi-Qiang], Savvides, M.[Marios], Cheng, K.T.[Kwang-Ting],
Reactnet: Towards Precise Binary Neural Network with Generalized Activation Functions,
ECCV20(XIV:143-159).
Springer DOI 2011
BibRef

Kim, D.[Dahyun], Singh, K.P.[Kunal Pratap], Choi, J.H.[Jong-Hyun],
Learning Architectures for Binary Networks,
ECCV20(XII: 575-591).
Springer DOI 2010
BibRef

Phan, H.[Hai], Huynh, D.[Dang], He, Y.[Yihui], Savvides, M.[Marios], Shen, Z.Q.[Zhi-Qiang],
MoBiNet: A Mobile Binary Network for Image Classification,
WACV20(3442-3451)
IEEE DOI 2006
Neural networks, Training, Computational modeling, Standards, Task analysis, Computational efficiency BibRef

Phan, H.[Hai], Liu, Z.C.[Ze-Chun], Huynh, D.[Dang], Savvides, M.[Marios], Cheng, K.T.[Kwang-Ting], Shen, Z.Q.[Zhi-Qiang],
Binarizing MobileNet via Evolution-Based Searching,
CVPR20(13417-13426)
IEEE DOI 2008
Convolution, Neural networks, Computational modeling, Training, Task analysis, Aerospace electronics BibRef

Bethge, J., Yang, H., Meinel, C.,
Training Accurate Binary Neural Networks from Scratch,
ICIP19(899-903)
IEEE DOI 1910
Binary Neural Networks BibRef

Bethge, J.[Joseph], Bartz, C.[Christian], Yang, H.J.[Hao-Jin], Chen, Y.[Ying], Meinel, C.[Christoph],
MeliusNet: An Improved Network Architecture for Binary Neural Networks,
WACV21(1438-1447)
IEEE DOI 2106
Convolutional codes, Adaptation models, Computational modeling, Neural networks, Computer architecture BibRef

Bethge, J., Yang, H., Bornstein, M., Meinel, C.,
BinaryDenseNet: Developing an Architecture for Binary Neural Networks,
NeruArch19(1951-1960)
IEEE DOI 2004
computational complexity, neural net architecture, binary neural networks, BNNs, computational memory costs, binary densenet BibRef

Xu, Y.H.[Ying-Hao], Dong, X.[Xin], Li, Y.D.[Yu-Dian], Su, H.[Hao],
A Main/Subsidiary Network Framework for Simplifying Binary Neural Networks,
CVPR19(7147-7155).
IEEE DOI 2002
BibRef

Shen, M., Han, K., Xu, C., Wang, Y.,
Searching for Accurate Binary Neural Architectures,
NeruArch19(2041-2044)
IEEE DOI 2004
evolutionary computation, mobile computing, neural nets, search problems, mobile devices, binary weights, neural architecture search BibRef

Prabhu, A.[Ameya], Batchu, V.[Vishal], Gajawada, R.[Rohit], Munagala, S.A.[Sri Aurobindo], Namboodiri, A.[Anoop],
Hybrid Binary Networks: Optimizing for Accuracy, Efficiency and Memory,
WACV18(821-829)
IEEE DOI 1806
approximation theory, data compression, image classification, image coding, image representation, Quantization (signal) BibRef

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Adversarial Networks, Adversarial Inputs, Generative Adversarial .