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Scaling Laws for Galaxy Images
April 5, 2024, 4:44 a.m. | Mike Walmsley, Micah Bowles, Anna M. M. Scaife, Jason Shingirai Makechemu, Alexander J. Gordon, Annette M. N. Ferguson, Robert G. Mann, James Pearson,
cs.CV updates on arXiv.org arxiv.org
Abstract: We present the first systematic investigation of supervised scaling laws outside of an ImageNet-like context - on images of galaxies. We use 840k galaxy images and over 100M annotations by Galaxy Zoo volunteers, comparable in scale to Imagenet-1K. We find that adding annotated galaxy images provides a power law improvement in performance across all architectures and all tasks, while adding trainable parameters is effective only for some (typically more subjectively challenging) tasks. We then compare …
abstract annotations arxiv astro-ph.ga context cs.cv galaxy imagenet images improvement investigation law laws power scale scaling type
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