Abstract: Weakly supervised image segmentation with image-level labels has drawn attention due to the high cost of pixel-level annotations. Traditional methods using Class Activation Maps (CAMs) often ...

Overview OpenCV courses on Coursera provide hands-on, career-ready skills for real-world computer vision ...

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 ...

Code repository for training a brain tumour U-Net 3D image segmentation model using the 'Task1 Brain Tumour' medical segmentation decathlon challenge dataset.

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 ...

Abstract: Recent studies have explored image segmentation for landmark detection in computer vision and medical imaging of the lower limb, showing promising results. However, the proposed ...

To address the trade-off between segmentation performance and model lightweighting in computer-aided skin lesion segmentation, this paper proposes a lightweight network architecture, Multi-Conv ...