Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive ...
Abstract: The Segment Anything Model (SAM) has gained renown for its success in image segmentation, benefiting significantly from its pretraining on extensive datasets and its interactive prompt-based ...
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 ...
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.
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