Simulating Fractional Stride Decrease in Binary Neural Networks Using Exponential and Logarithmic Decay: A Comparative Experiment in Energy-Efficient BNN Design

This paper takes a novel approach to simulating fractional stride decreases in binary neural networks (BNNs), addressing the limitations of fixed integer strides typically used in traditional convolutional neural networks (CNNs). By introducing a dynamic stride adjustment mechanism that reduces stri... View More