Abstract: Semantic segmentation of high-resolution remote sensing images (RSIs) remains challenging due to the degradation of high-frequency (HF) semantic cues during convolutional encoding and the ...

Abstract: Semantic segmentation consists of predicting a semantic label for each image pixel. While existing deep learning approaches achieve high accuracy, they often overlook the ordinal ...

Microsoft says Agent Framework 1.0 is the production-ready release, with stable APIs and long-term support for both .NET and Python. The framework is presented as a unified successor path that builds ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Dany Lepage discusses the architectural ...

For startups and established businesses, understanding the importance of segmentation is essential for the granular analysis of consumer demographics, behaviors, needs, and preferences. These insights ...

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 ...

Soon, you might not need to type in the exact name or spelling for searches in File Explorer, Settings, or Windows Search. But like with many AI-powered features, this one still needs work. Here's how ...

If you want to improve the way Windows Search works on your computer, we recommend you use Semantic Search. It is a new feature introduced in Windows 11, allowing Windows to leverage AI to search ...

With agentic AI now firmly established as a key component of modern software development, Microsoft graduated its Semantic Kernel Agent Framework to Release Candidate 1 status. That was announced last ...

Good businesses know that customer segmentation is a necessity. It’s used for everything from market strategies to discount offers to developing loyalty programs. The more accurate the segmentation is ...