Speed Optimization of Convolutional Neural Networks (CNNs) on FPGA for Real-Time Image Classification
Year: 2024
Type: article
Abstract: This research paper investigates the optimization techniques employed in implementing Convolutional Neural Networks (CNNs) on Field-Programmable Gate Arrays (FPGAs) to achieve real-time image classification. CNNs have demonstrated remarkable success in various image recognition tasks, but their deployment on resource- constrained platforms like FPGAs presents unique challenges. This paper explores methods to overcome these challenges and maximize the efficiency of CNN inference on FPGAs.
Authors: Prajwal Hiremath, K B Ramesh
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6967853025
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