SOURCE-LINKED INTELLIGENCE
Rethinking Image Processing for the Age of AI: A Problem-First Framework for Scientific Progress
Modern AI has greatly expanded the capabilities of image processing. However, the ready availability of powerful models, public datasets, and benchmark leaderboards has also en- couraged a model-first research pattern: researchers increasingly begin with an available architecture and optimize it on a public benchmark, rather than beginning with the underlying real-world imaging problem. This can produce impressive benchmark results without necessarily improving our understanding or solution of the real problem. This paper argues for a problem-first approach that distinguishes the physical imag
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-27T09:05:39.000Z
First collected: 2026-09-21T08:51:59.673Z. This is not the publication date.