Neural Network Architectures for Real-Time Image Processing

Abstract

This research introduces novel neural network architectures optimized for real-time image processing tasks. By focusing on speed and accuracy, the study addresses the computational demands of applications such as autonomous vehicles and video surveillance. The proposed architectures demonstrate significant improvements in processing speeds, enabling real-time analysis without compromising on result accuracy.
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