CIFAR-10 problems analyze crude 32 x 32 color images to predict which of 10 classes the image is. Here, Dr. James McCaffrey of Microsoft Research shows how to create a PyTorch image classification ...
In pathological diagnostics, histological images highlight the oncological features of excised specimens, but they require laborious and costly staining procedures. Despite recent innovations in label ...
Achieving high-precision pixel-level segmentation in medical imaging necessitates both the preservation of fine-grained local details and the modeling of long-range contextual dependencies; ...
PyTorch 1.10 is production ready, with a rich ecosystem of tools and libraries for deep learning, computer vision, natural language processing, and more. Here's how to get started with PyTorch.
Some results have been hidden because they may be inaccessible to you
Show inaccessible results