Abstract: Tumor segmentation is crucial for surgical planning and precise tumor resection for effective treatment. Traditionally, tumor localization has been performed using medical imaging techniques ...

Abstract: The success of deep learning in 3D medical image segmentation hinges on training with a large dataset of fully annotated 3D volumes, which are difficult and time-consuming to acquire.

Earlier this week, some people on X began replying to photos with a very specific kind of request. “Put her in a bikini,” “take her dress off,” “spread her legs,” and so on, they commanded Grok, the ...

This project demonstrates instance segmentation using Mask R-CNN with the OpenCV DNN module. The model is pre-trained on the COCO dataset and can detect and segment multiple object classes in images.

AI is the broad goal of creating intelligent systems, no matter what technique is used. In comparison, Machine Learning is a specific technique to train intelligent systems by teaching models to learn ...

Abstract: Recently, multilayer perceptron (MLPs)-based methods in computer vision have attracted much attention due to the ability of learning long-range dependencies. However, MLPs-based methods ...