combining multiple deep learning models, such as integrating Mask R-CNN with YOLO, could help reduce false detection rates. Furthermore, repeated road inspections can improve the accuracy of ...

Abstract: Aiming at the problems of low detection accuracy and large model of most current printed circuit board (PCB) defect detection algorithms, which are not conducive to mobile deployment, an ...

MCHNet-RF2D outperforms existing CNN-Transformer hybrid networks by 2.8% and surpasses current fastener defect detection algorithms by 2.9%. In practical deployment on over 40 trains, our model ...

This study reviews recent advancements in CNN-based ... improved model interpretability and robust DR detection, highlighting deep learning’s potential for clinical use and suggesting future ...

The introduction of Anthropic’s hybrid model, which combines multiple reasoning approaches to solve complex problems more effectively, comes amid fierce competition in AI development, with US ...

Abstract: A printed circuit board (PCB) surface-mounted devices (SMDs) defect detection algorithm based on random forest (RF ... geometric correction, component positioning, and image denoising.