Abstract: Accurate medical image segmentation is essential for effective diagnosis and treatment. Previously we proposed PraNet-V1 as a means to enhance polyp segmentation, introducing a reverse ...
Abstract: Recently, single-source domain generalization (SDG) has gained popularity in medical image segmentation. As a prominent technique, adversarial image augmentation technique can generate ...
Meta Platforms Inc. today is expanding its suite of open-source Segment Anything computer vision models with the release of SAM 3 and SAM 3D, introducing enhanced object recognition and ...
In this tutorial, we build an Advanced OCR AI Agent in Google Colab using EasyOCR, OpenCV, and Pillow, running fully offline with GPU acceleration. The agent includes a preprocessing pipeline with ...
A research team led by Prof. WANG Huanqin at the Institute of Intelligent Machines, the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, recently proposed a semi-supervised ...
def getImg(url): request = urllib.request.Request(url, headers={"User-Agent": "Mozilla/5.0"}) return cv2.imdecode(np.frombuffer(request.read(), dtype=np.uint8), cv2 ...
Medical image segmentation is at the heart of modern healthcare AI, enabling crucial tasks such as disease detection, progression monitoring, and personalized treatment planning. In disciplines like ...
Laryngeal high-speed video (HSV) is a widely used technique for diagnosing laryngeal diseases. Among various analytical approaches, segmentation of glottis regions has proven effective in evaluating ...
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