Abstract: For image-related deep learning tasks, the first step often involves reading data from external storage and performing preprocessing on the CPU. As accelerator speed increases and the number ...

Accurate preprocessing of functional magnetic resonance imaging (fMRI) data is crucial for effective analysis in preclinical studies. Key steps such as denoising, skull-stripping, and affine ...

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ABSTRACT: Image segmentation is a fundamental process in digital image analysis, with applications in object recognition, medical imaging, and computer vision. Traditional segmentation techniques ...

Abstract: In this work, one-shot integer-forcing source coding (IFSC) is considered. We assess preprocessing approaches prior to encoding to improve the performance. Two approaches are presented to ...

This request was rejected before here (#1523) because preprocessing the image is not useful for OCR accuracy anymore. I agree with this. However preprocessing can still be beneficial for image ...

I've been using it to run evaluations on public models, and have found slight variations in model performance on ICL tasks (haven't test all the other tasks yet) across runs. Upon examining the code, ...