Medical image segmentation, the task of tracing the exact outlines of lesions, polyps, and blood vessels in clinical scans, has long been dominated by a trade-off. Convolutional networks excel at ...

import io import os import re import sys import time import shutil import logging import textwrap import subprocess from pathlib import Path INSTALL_JBIG2 = True def sh(cmd: str, check: bool = True) ...

Artificial Intelligence has evolved from science fiction to the backbone of modern technology. In 2025, AI powers 85% of customer interactions, drives $15.7 trillion in global economic impact, and ...

Human pose estimation is a cutting-edge computer vision technology that transforms visual data into actionable insights about human movement. By utilizing advanced machine learning models like ...

Gemma is a collection of lightweight open source generative AI (GenAI) models. Gemma was created by the Google DeepMind research lab that also developed closed source Gemini, Google's generative AI ...

Segment Anything Model 2 (SAM 2) is a foundation model towards solving promptable visual segmentation in images and videos. We extend SAM to video by considering images as a video with a single frame.

The performance gap between unsupervised segmentation models and SAM can be significantly reduced. UnSAM not only advances the state-of-the-art in unsupervised segmentation by 10% but also achieves ...

Deploying YOLOv8 on Raspberry Pi Zero 2W for Real-Time Bee Counting at the Hive Entrance. Why is this important? Bee populations are vital indicators of environmental health, and their monitoring can ...

Please go to "Colab_BEFUnet.ipynb" for complete detail on dataset preparation and Train/Test procedure or follow the instructions below. Run the below code to train BEFUnet on the synapse dataset.