Integrating deep learning in optical microscopy enhances image analysis, overcoming traditional limitations and improving classification and segmentation tasks.

The YOLOv8 and Swin Transformer dual-module system significantly improves structural crack detection, offering a faster and more accurate inspection method.

Robots are rapidly moving beyond pre-programmed automation into a new era of adaptive, learning-driven autonomy. At the center of this ...

Abstract: On-road obstacle detection and classification is one of the key tasks in the perception system of self-driving vehicles. Since vehicle tracking involves localizationand association of ...

Abstract: The existing LiDAR-based obstacle detection methods for autonomous rail auxiliary transportation vehicles in underground coal mines are hindered by inaccurate detection and frequent ...

Melanoma remains one of the hardest skin cancers to diagnose because it often mimics harmless moles or lesions. While most artificial intelligence (AI) tools rely on dermoscopic images alone, they ...

Deep Trekker Revolution ROV at Exercise ‘Dynamic Messenger/REPMUS 25'. The Viper mine disruption system is deployed underneath the front of the ROV. (Janes/Neil Dee) Canadian remotely operated vehicle ...

ABSTRACT: Timely and accurate detection of plant diseases is essential for improving crop yields and ensuring food security, particularly in regions like Cameroon, where farmers often rely on visual ...

DJI's obstacle avoidance system could be just as useful on land as it is in the air. DJI, known for its dominance in the drone market, has entered the smart home world with a range of robot vacuums ...