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Training Binarized Neural Networks Using Ternary Multipliers
IEEE Design & Test, 2021Deep learning offers the promise of intelligent devices that are able to perceive, reason and take intuitive actions. The rising adoption of deep learning techniques has motivated researchers and developers to seek low-cost and high-speed software/hardware solutions for deployment on smart devices.
Amir Ardakani +2 more
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Binarized Neural Network with Stochastic Memristors
2019 IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS), 2019This paper proposes the analog hardware implementation of Binarized Neural Network (BNN). Most of the existing hardware implementations of neural networks do not consider the memristor variability issue and its effect on the overall system performance.
Olga Krestinskaya +2 more
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Error-Diffusion Binarization for Neural Networks
1997In optical implementation of neural networks, binarization is often a necessity. Error-diffusion (ED) is presented has a more reliable binarization technic over hardclipping. We use a simple self-organizing learning algorithm for its demonstration.
André Granger +2 more
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Weight Isolation-Based Binarized Neural Networks Accelerator
2020 IEEE International Symposium on Circuits and Systems (ISCAS), 2020In this paper, we introduce a binary neural network accelerator which using a new binarization method and hardware sparse. We propose the weights and the activations to either 1 or 0 instead of +1 or −1, which makes the convolution process simplified and more suitable for hardware implementation.
Zhangkong Xian, Hongge Li, Yuliang Li
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Waste Sorting System Using Binarized Neural Network
2020 International Conference on Intelligent Computing, Automation and Systems (ICICAS), 2020Garbage classification is of great importance to reduce environmental pollution and resource waste. For the sake of realizing efficient waste sorting and treatment, we propose a low latency automatic waste sorting system, which can classify garbage into the four categories: recyclable, harmful, kitchen and other garbage, and put the classified garbage ...
Mingmei Wu +5 more
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FBNA: A Fully Binarized Neural Network Accelerator
2018 28th International Conference on Field Programmable Logic and Applications (FPL), 2018In recent researches, binarized neural network (BNN) has been proposed to address the massive computations and large memory footprint problem of the convolutional neural network (CNN). Several works have designed specific BNN accelerators and showed very promising results. Nevertheless, only part of the neural network is binarized in their architecture
Peng Guo +5 more
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Neural networks for binarizing computer-generated holograms
Optics Communications, 1991Abstract A Hopfield type neural network was applied to compute synthetic, binary holograms. This iterative neuron algorithm minimizes reconstruction errors in amplitude and phase. About twenty iteration steps are sufficient for convergence, each of them has the computational complexity of a FFT.
D. Just, D.T. Ling
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Memristor Binarized Neural Networks
JOURNAL OF SEMICONDUCTOR TECHNOLOGY AND SCIENCE, 2018Khoa Van Pham +7 more
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Binarized SNNs: Efficient and Error-Resilient Spiking Neural Networks through Binarization
2021 IEEE/ACM International Conference On Computer Aided Design (ICCAD), 2021Ming-Liang Wei +5 more
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Evaluating FPGA Acceleration on Binarized Neural Networks and Quantized Neural Networks
2022 International Symposium on Measurement and Control in Robotics (ISMCR), 2022Sarala K Surapally +3 more
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