Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive ...

Abstract: Acquiring high-quality annotated data for medical image segmentation is tedious and costly. Semi-supervised segmentation techniques alleviate this burden by leveraging unlabeled data to ...

Abstract: Medical image segmentation has made significant strides with the development of basic models. Specifically, models that combine CNNs with transformers can successfully extract both local and ...

The goal of the project is to inference a deep learning semantic segmentation model on a webcam video stream in Linux in order to remove background and provide a clean video stream with a person only.

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.