Power Efficient Design of High-Performance Convolutional Neural Networks Hardware Accelerator on FPGA: A Case Study With GoogLeNet

Power Efficient Design of High-Performance Convolutional Neural Networks Hardware Accelerator on FPGA: A Case Study With GoogLeNet

Convolutional neural networks (CNNs) have dominated image recognition and object detection models in the last few years. They can achieve the highest accuracies with several applications such as automotive and biomedical applications. CNNs are usually implemented by using Graphical Processing Units...

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Bibliographic Details
Main Authors: Ahmed J. Abd El-Maksoud, Mohamed Ebbed, Ahmed H. Khalil, Hassan Mostafa
Format: article
Language:EN
Published: IEEE 2021
Subjects:
Convolutional neural networks (CNNs)
field programmable gate arrays (FPGAs)
GoogLeNet
hardware accelerators
object classification
parallel computing
Electrical engineering. Electronics. Nuclear engineering
TK1-9971
Online Access:https://doaj.org/article/76953a014d404d07a2d8a929652c98f7
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https://doaj.org/article/76953a014d404d07a2d8a929652c98f7

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