A comprehensive review of binary neural network

C Yuan, SS Agaian - Artificial Intelligence Review, 2023 - Springer
Deep learning (DL) has recently changed the development of intelligent systems and is
widely adopted in many real-life applications. Despite their various benefits and potentials …

A systematic literature review on binary neural networks

R Sayed, H Azmi, H Shawkey, AH Khalil… - IEEE Access, 2023 - ieeexplore.ieee.org
This paper presents an extensive literature review on Binary Neural Network (BNN). BNN
utilizes binary weights and activation function parameters to substitute the full-precision …

AWB-GCN: A graph convolutional network accelerator with runtime workload rebalancing

T Geng, A Li, R Shi, C Wu, T Wang, Y Li… - 2020 53rd Annual …, 2020 - ieeexplore.ieee.org
Deep learning systems have been successfully applied to Euclidean data such as images,
video, and audio. In many applications, however, information and their relationships are …

Fpga-based deep learning inference accelerators: Where are we standing?

A Nechi, L Groth, S Mulhem, F Merchant… - ACM Transactions on …, 2023 - dl.acm.org
Recently, artificial intelligence applications have become part of almost all emerging
technologies around us. Neural networks, in particular, have shown significant advantages …

Accelerating binarized neural networks via bit-tensor-cores in turing gpus

A Li, S Su - IEEE Transactions on Parallel and Distributed …, 2020 - ieeexplore.ieee.org
Despite foreseeing tremendous speedups over conventional deep neural networks, the
performance advantage of binarized neural networks (BNNs) has merely been showcased …