Hospitals do not always have the opportunity to collect data in tidy, uniform batches. A clinic may have a handful of ...
To overcome two challenges in training AI – scarce or hard-to-get data and data privacy – researchers have come up with a ...
Abstract: Data Augmentation (DA), i.e., synthesizing faithful and diverse samples to expand the original training set, is an effective strategy to improve the performance of various data-scarce tasks.
Abstract: Imbalanced datasets pose significant challenges to the reliability and robustness of visual classification systems, particularly in critical applications like solar panel dust detection.
Overview: Python dominates computer vision with its vast array of open-source libraries and active community support.These ...
[ECCV 2024] Official implementation of "Every Pixel Has its Moments: Ultra-High-Resolution Unpaired Image-to-Image Translation via Dense Normalization" Multiview matching with deep-learning and ...
A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications.
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