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A survey on neural network hardware accelerators
Artificial intelligence (AI) hardware accelerator is an emerging research for several
applications and domains. The hardware accelerator's direction is to provide high …
applications and domains. The hardware accelerator's direction is to provide high …
Fully parallel stochastic computing hardware implementation of convolutional neural networks for edge computing applications
CF Frasser, P Linares-Serrano… - … on Neural Networks …, 2022 - ieeexplore.ieee.org
Edge artificial intelligence (AI) is receiving a tremendous amount of interest from the
machine learning community due to the ever-increasing popularization of the Internet of …
machine learning community due to the ever-increasing popularization of the Internet of …
Power-intent systolic array using modified parallel multiplier for machine learning acceleration
Systolic arrays are an integral part of many modern machine learning (ML) accelerators due
to their efficiency in performing matrix multiplication that is a key primitive in modern ML …
to their efficiency in performing matrix multiplication that is a key primitive in modern ML …
A high-performance pixel-level fully pipelined hardware accelerator for neural networks
Z Li, Z Zhang, J Hu, Q Meng, X Shi… - … on Neural Networks …, 2024 - ieeexplore.ieee.org
The design of convolutional neural network (CNN) hardware accelerators based on a single
computing engine (CE) architecture or multi-CE architecture has received widespread …
computing engine (CE) architecture or multi-CE architecture has received widespread …
DCP-CNN: Efficient Acceleration of CNNs With Dynamic Computing Parallelism on FPGA
K Dai, Z ** of Downward Shortwave Radiation from GOES-R Using Gradient Boosting
This study investigates high-frequency map** of downward shortwave radiation (DSR) at
the Earth's surface using the advanced baseline imager (ABI) instrument mounted on …
the Earth's surface using the advanced baseline imager (ABI) instrument mounted on …
Table-Lookup MAC: Scalable Processing of Quantised Neural Networks in FPGA Soft Logic
D Gerlinghoff, BCM Choong, RSM Goh… - Proceedings of the …, 2024 - dl.acm.org
Recent advancements in neural network quantisation have yielded remarkable outcomes,
with three-bit networks reaching state-of-the-art full-precision accuracy in complex tasks …
with three-bit networks reaching state-of-the-art full-precision accuracy in complex tasks …
Fast inner-product algorithms and architectures for deep neural network accelerators
We introduce a new algorithm called the Free-pipeline Fast Inner Product (FFIP) and its
hardware architecture that improve an under-explored fast inner-product algorithm (FIP) …
hardware architecture that improve an under-explored fast inner-product algorithm (FIP) …
Accelerating Bayesian neural networks via algorithmic and hardware optimizations
Bayesian neural networks (BayesNNs) have demonstrated their advantages in various
safety-critical applications, such as autonomous driving or healthcare, due to their ability to …
safety-critical applications, such as autonomous driving or healthcare, due to their ability to …