A Single Graph Convolution Is All You Need: Efficient Grayscale Image Classification

Image classifiers often rely on convolutional neural networks (CNN) for their tasks, which are inherently more heavyweight than multilayer perceptrons (MLPs), which can be problematic in real-time applications. Additionally, many image classification models work on both RGB and grayscale datasets. Classifiers that operate solely on grayscale images are much less common. Grayscale image classification has diverse applications, including but not limited to medical image classification and synthetic aperture radar (SAR) automatic target recognition (ATR). Thus, we present a novel grayscale …

applications classification classifiers cnn convolution convolutional neural networks cs.cv cs.lg datasets graph image images networks neural networks real-time real-time applications tasks work