Looking for papers on feature engineering for computer vision

What the title says. I'm looking for papers or literature reviews on feature engineering techniques for machine learning applications. I'm building a semantic segmentation system on random forests which uses optical and infrared imagery, and it's obviously lacking in terms of performance compared to a deep learning approach (e.g. a UNET). I was wondering if some engineered features would improve the performance. I searched arxiv, but got thousands of irrelevant results. Please, no suggestions for changing my workflow. Thanks!

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