Overview AI systems use sensors and computer vision to detect pests and diseases early, reducing crop damage and yield losses ...

CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...

Abstract: Deep learning models in computer vision face challenges such as high computational resource demands and limited generalization in practical scenarios. To address these issues, this study ...

A warehouse manager showed me his "secret weapon": Excel. He was a wiz; he knew all the tricks. But I kept thinking this single Excel file was the only thing connecting a $2 million monthly operation ...

DINOv3 represents a major leap in computer vision: its frozen universal backbone and SSL approach enable researchers and developers to tackle annotation-scarce tasks, deploy high-performance models ...

Abstract: We introduce a new perspective and a theory, called Quantum Vision (QV) theory in deep learning, for object recognition. The proposed theory is based on particle-wave duality of quantum ...

Computer vision continues to be one of the most dynamic and impactful fields in artificial intelligence. Thanks to breakthroughs in deep learning, architecture design and data efficiency, machines are ...

Introduction: Accurate and automated fruit classification plays a vital role in modern agriculture but remains challenging due to the wide variability in fruit appearances. Methods: In this study, we ...

We are excited to share our first big milestone in solving a grand challenge that has hampered the predictive power of computational chemistry, biochemistry, and materials science for decades. By ...