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

By Jacob Fein-Ashley and others at
LogoIMAG
and
LogoUniversity of Southern California
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... Show more
May 14, 2024
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