Semantic segmentation of remote sensing images is pivotal for comprehensive Earth observation, but the demand for interpreting new object categories, coupled with the high expense of manual annotation ...

Sometimes, reading Python code just isn’t enough to see what’s really going on. You can stare at lines for hours and still miss how variables change, or why a bug keeps popping up. That’s where a ...

Introduction: Weeds compete with crops for water, nutrients, and light, negatively impacting maize yield and quality. To enhance weed identification accuracy and meet the requirements of precision ...

Abstract: Semantic segmentation in remote sensing images (RSIs) assigns unique semantic labels to each pixel and plays a crucial role in real-world applications such as environmental change monitoring ...

The Amazon rainforest, a vital global carbon sink, is under increasing threat from rising temperatures, prolonged droughts, deforestation, and wildfires. Timely, accurate monitoring of forest cover is ...

Abstract: To address complex semantic segmentation in coal mine areas, this study proposes the SAM-SEF (SAM-based Semantic Enhancement Framework). It integrates Semantic-SAM’s zero-shot segmentation ...

Modern software engineering faces growing challenges in accurately retrieving and understanding code across diverse programming languages and large-scale codebases. Existing embedding models often ...

Would you trust an AI agent to run unverified code on your system? For developers and AI practitioners, this question isn’t just hypothetical—it’s a critical challenge. The risks of executing ...

Search engines have come a long way from relying on exact match keywords. Today, they try to understand the meaning behind content — what it says, how it says it, and whether it truly answers the ...