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   Articles with "binary neural" as a keyword



A Deep Learning Accelerator Based on a Streaming Architecture for Binary Neural Networks

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recommendations! Published in 2022 at "IEEE Access"

DOI: 10.1109/access.2022.3151916

Abstract: Deep neural networks (DNNs) have played an increasingly important role in various areas such as computer vision and voice recognition. While training and validation become gradually feasible with high-end general-purpose processors such as graphical processor… read more here.

Keywords: deep learning; neural networks; binary neural; streaming architecture ... See more keywords

“Ghost” and Attention in Binary Neural Network

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recommendations! Published in 2022 at "IEEE Access"

DOI: 10.1109/access.2022.3181192

Abstract: As the memory footprint requirement and computational scale concerned, the light-weighted Binary Neural Networks (BNNs) have great advantages in limited-resources platforms, such as AIoT (Artificial Intelligence in Internet of Things) edge terminals, wearable and portable… read more here.

Keywords: network; accuracy; ghost; binary neural ... See more keywords

STT-BNN: A Novel STT-MRAM In-Memory Computing Macro for Binary Neural Networks

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recommendations! Published in 2022 at "IEEE Journal on Emerging and Selected Topics in Circuits and Systems"

DOI: 10.1109/jetcas.2022.3169759

Abstract: This paper presents a novel architecture for in-memory computation of binary neural network (BNN) workloads based on STT-MRAM arrays. In the proposed architecture, BNN inputs are fed through bitlines, then, a BNN vector multiplication can… read more here.

Keywords: bnn; stt mram; stt bnn; bnn novel ... See more keywords

Always-On 674μ W@4GOP/s Error Resilient Binary Neural Networks With Aggressive SRAM Voltage Scaling on a 22-nm IoT End-Node

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recommendations! Published in 2020 at "IEEE Transactions on Circuits and Systems I: Regular Papers"

DOI: 10.1109/tcsi.2020.3012576

Abstract: Binary Neural Networks (BNNs) have been shown to be robust to random bit-level noise, making aggressive voltage scaling attractive as a power-saving technique for both logic and SRAMs. In this work, we introduce the first… read more here.

Keywords: voltage scaling; binary neural; voltage; neural networks ... See more keywords

BiNPU: A 33.0 MOP/s/LUT Binary Neural Network Inference Processor Showing 88.26% CIFAR10 Accuracy With 1.9 Mbit On-Chip Parameters in a 28-nm FPGA

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recommendations! Published in 2024 at "IEEE Transactions on Circuits and Systems II: Express Briefs"

DOI: 10.1109/tcsii.2024.3440965

Abstract: An efficient processor to perform inference of binary neural networks (BNNs) is presented. The proposed processor, named BiNPU, is designed based on a unified architecture that can efficiently process BNN modules of various types, including… read more here.

Keywords: inference; chip; processor; accuracy mbit ... See more keywords

Universal Binary Neural Networks Design by Improved Differentiable Neural Architecture Search

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recommendations! Published in 2024 at "IEEE Transactions on Circuits and Systems for Video Technology"

DOI: 10.1109/tcsvt.2024.3398691

Abstract: Binary Neural Networks (BNNs) using 1-bit weights and activations are emerging as a promising approach for mobile devices and edge computing platforms. Concurrently, traditional Neural Architecture Search (NAS) has gained widespread usage in automatically designing… read more here.

Keywords: universal binary; neural architecture; architecture search; binary neural ... See more keywords

SecBNN: Efficient Secure Inference on Binary Neural Networks

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recommendations! Published in 2024 at "IEEE Transactions on Information Forensics and Security"

DOI: 10.1109/tifs.2024.3484936

Abstract: This work studies secure inference on Binary Neural Networks (BNNs), which have binary weights and activations as a desirable feature. Although previous works have developed secure methodologies for BNNs, they still have performance limitations and… read more here.

Keywords: inference; secure; secure inference; neural networks ... See more keywords

MOL-Based In-Memory Computing of Binary Neural Networks

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recommendations! Published in 2022 at "IEEE Transactions on Very Large Scale Integration (VLSI) Systems"

DOI: 10.1109/tvlsi.2022.3163233

Abstract: Convolutional neural networks (CNNs) have proven very effective in a variety of practical applications involving artificial intelligence (AI). However, the layer depth of CNN deepens as user applications become more sophisticated, resulting in a huge… read more here.

Keywords: neural networks; mol based; based memory; binary neural ... See more keywords

Long-Term Accuracy Enhancement of Binary Neural Networks Based on Optimized Three-Dimensional Memristor Array

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recommendations! Published in 2022 at "Micromachines"

DOI: 10.3390/mi13020308

Abstract: In embedded neuromorphic Internet of Things (IoT) systems, it is critical to improve the efficiency of neural network (NN) edge devices in inferring a pretrained NN. Meanwhile, in the paradigm of edge computing, device integration,… read more here.

Keywords: long term; neural networks; accuracy; three dimensional ... See more keywords

LDF-BNN: A Real-Time and High-Accuracy Binary Neural Network Accelerator Based on the Improved BNext

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recommendations! Published in 2024 at "Micromachines"

DOI: 10.3390/mi15101265

Abstract: Significant progress has been made in industrial defect detection due to the powerful feature extraction capabilities of deep neural networks (DNNs). However, the high computational cost and memory requirement of DNNs pose a great challenge… read more here.

Keywords: ldf bnn; accelerator; high accuracy; accuracy ... See more keywords