Bibench: Benchmarking and analyzing network binarization
Network binarization emerges as one of the most promising compression approaches
offering extraordinary computation and memory savings by minimizing the bit-width …
offering extraordinary computation and memory savings by minimizing the bit-width …
A review of recent advances of binary neural networks for edge computing
Edge computing is promising to become one of the next hottest topics in artificial intelligence
because it benefits various evolving domains, such as real-time unmanned aerial systems …
because it benefits various evolving domains, such as real-time unmanned aerial systems …
Visual wake words dataset
The emergence of Internet of Things (IoT) applications requires intelligence on the edge.
Microcontrollers provide a low-cost compute platform to deploy intelligent IoT applications …
Microcontrollers provide a low-cost compute platform to deploy intelligent IoT applications …
unzipFPGA: Enhancing FPGA-based CNN engines with on-the-fly weights generation
Single computation engines have become a popular design choice for FPGA-based
convolutional neural networks (CNNs) enabling the deployment of diverse models without …
convolutional neural networks (CNNs) enabling the deployment of diverse models without …
Toward Efficient Convolutional Neural Networks With Structured Ternary Patterns
C Kyrkou - IEEE Transactions on Neural Networks and …, 2024 - ieeexplore.ieee.org
High-efficiency deep learning (DL) models are necessary not only to facilitate their use in
devices with limited resources but also to improve resources required for training …
devices with limited resources but also to improve resources required for training …
Mitigating Memory Wall Effects in CNN Engines with On-the-Fly Weights Generation
The unprecedented accuracy of convolutional neural networks (CNNs) across a broad
range of AI tasks has led to their widespread deployment in mobile and embedded settings …
range of AI tasks has led to their widespread deployment in mobile and embedded settings …
Towards lossless binary convolutional neural networks using piecewise approximation
Abstract Binary Convolutional Neural Networks (CNNs) can significantly reduce the number
of arithmetic operations and the size of memory storage, which makes the deployment of …
of arithmetic operations and the size of memory storage, which makes the deployment of …
On-the-fly deterministic binary filters for memory efficient keyword spotting applications on embedded devices
Lightweight keyword spotting (KWS) applications are often used to trigger the execution of
more complex speech recognition algorithms that are computationally demanding and …
more complex speech recognition algorithms that are computationally demanding and …
[書籍][B] Binary Neural Networks: Algorithms, Architectures, and Applications
Deep learning has achieved impressive results in image classification, computer vision, and
natural language processing. To achieve better performance, deeper and wider networks …
natural language processing. To achieve better performance, deeper and wider networks …
Binary Neural Networks
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