A new version of Cellpose —the popular tool that maps the boundaries of diverse cells in microscopy images —now works on less-than-perfect pictures that are noisy, blurry, or undersampled.

DSA Club Seminar w/ Dr. Deepak Devegowda on Vision Transformers for Image Segmentation. Tuesday, February 11th, from 5-6:15 pm in Sarkeys M204. Free food will be provided, and 10 free ...

Adolphi, C. and Sosonkina, M. (2025) Machine Learning and Simulation Techniques for Detecting Buoy Types from LiDAR Data.

Radiologists are beginning to use AI-based computer vision models to help speed up the laborious process of parsing medical ...

We torture-test a dozen of the most popular text-to-image AI tools with a series of prompts designed to highlight their strengths and weaknesses. Here's how they stack up. I've been writing about ...

Abstract: Segment Anything Model (SAM) is a foundational image segmentation model, which shows superior performance for natural image segmentation tasks. Several SAM-based medical image segmentations ...

Abstract: To address the issue of inaccurate segmentation caused by blurred edges and strong noise in thyroid nodule ultrasound images, an image segmentation method based on an improved Swin ...

Scientists claim to have established a deep learning device that can exactly predict image retargeting dimensions an automate cropping and resizing ...

Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks in Semantic Segmentation, Interactive Segmentation, Panoptic Segmentation, Image ...

Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks in Semantic Segmentation, Interactive Segmentation, Panoptic Segmentation, Image ...