Image segmentation is one of those deceptively simple tasks that quietly underpins much of modern computer vision. Before a self-driving car can recognize a pedestrian, before a radiologist’s AI a ...

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 ...

Technology companies have been “running real-time, unregulated product testing on Australians” for too long, communications minister says. By Laura Chung Reporting from Sydney, Australia The ...

For years, social media giants controlled what users saw in their feeds. While people could follow accounts, like posts or hide content they didn’t enjoy, recommendation algorithms controlled what was ...

Abstract: Machine learning algorithm for multi-modal image segmentation is extensively employed in medical analysis and diagnosis. Clustering represents a mainstream approach for image segmentation, ...

In a previous post, I dove into some survey results to explain why segmentation has evolved into a foundational concept for network security. Specifically, I discussed how a dual segmentation approach ...

I design and deploy high-impact systems built on LLMs, local inference, and agent architectures. Most scientific algorithms live in MATLAB - image processing and analysis, machine learning ...

Automated apple harvesting is hindered by clustered fruits, varying illumination, and inconsistent depth perception in complex orchard environments. While deep learning models such as Faster R-CNN and ...

“If I could change one thing about my organization’s segmentation approach, it would definitely be to further automate and integrate our segmentation tools and processes. By leveraging automation and ...

Chinese tech giant ByteDance finalized its agreement to sell a majority stake in its video platform TikTok to a group of U.S. investors. TikTok announced on Jan. 22, 2026, that it has formed TikTok ...