Visual example of our conformal margin: we build a morphological margin (via dilation) that covers all missed pixels (false negatives). Dataset: WBC In the following image, we have a ground truth mask ...

Abstract: Tongue image segmentation is important in tongue diagnosis, oral disease diagnosis, and health monitoring in traditional Chinese medicine (TCM). Traditional image segmentation methods ...

Semantic segmentation is critical in medical image processing, with traditional specialist models facing adaptation challenges to new tasks or distribution shifts. While both generalist pre-trained ...

Google Colab, also known as Colaboratory, is a free online tool from Google that lets you write and run Python code directly in your browser. It works like Jupyter Notebook but without the hassle of ...

These methods often encounter issues of under-segmentation or over-segmentation and are sensitive to noise artifacts. Deep learning has been widely applied in teeth image segmentation, with its ...

Python libraries are pre-written collections of code designed to simplify programming by providing ready-made functions for specific tasks. They eliminate the need to write repetitive code and cover ...

Abstract: Image segmentation splits the original image into different non-overlapping parts to extract the desired region for various computer vision applications. Diverse methods exist to perform ...

The MHSAttResDU-Net incorporates RCC for complexity control and improved generalization under varying lighting. The SSRP unit in encoder-decoder blocks reduces feature map dimensions, capturing key ...

Monocular depth estimation involves predicting scene depth from a single RGB image—a fundamental task in computer vision with wide-ranging applications, including augmented reality, robotics, and 3D ...