Q Seg

Q-Seg, encompassing various approaches to image segmentation, aims to accurately and efficiently delineate objects or regions of interest within images and videos. Current research focuses on improving robustness to noise and artifacts, particularly in challenging domains like medical imaging and video analysis, employing techniques such as transformer-based networks, multimodal fusion (e.g., integrating audio cues), and quantum annealing algorithms. These advancements hold significant potential for applications ranging from automated medical diagnosis and surgical assistance to improved remote sensing and autonomous systems.