Researchers have evaluated how Vision Transformers and convolutional neural networks can support faster and more accurate ...

Abstract: Due to the fast development of the use of solar energy, it is necessary to efficiently maintain and manage the waste of solar panels. Solar energy has been a source of sustainable and widely ...

Variation is becoming a bigger problem in multi-die assemblies with TSVs and hybrid bonding. Multi-modal approaches are required to test these devices. AI plays a role in improving defect capture rate ...

In the 1992 film, “Sneakers,” a team of security specialists scans surveillance footage of Dr. Gunter Janek, a mathematician who’s invented a revolutionary codebreaker and hidden it in a black ...

Researchers propose a new alignment-aware state-space fusion framework called MambaAlign that produces tighter, less fragmented anomaly maps, and is substantially more robust to modest misalignment ...

Researchers from Stony Brook University, in collaboration with Ecosuite and Ecogy Energy, have developed a self-supervised machine-learning algorithm designed to identify physical anomalies in solar ...

This project uses deep learning techniques to detect malware by analyzing file characteristics, byte sequences, and behavioral patterns. It employs Convolutional Neural Networks (CNNs) for image-based ...

Researchers in China have developed a novel deep learning model to detect defects in photovoltaic panels. The approach leverages high-resolution visible light imaging to identify defects using an ...

1 Department of Computer Science, American International University-Bangladesh (AIUB), Dhaka, Bangladesh. 2 Department of Electrical and Electronics Engineering, American International ...

Abstract: An improved Faster R-CNN-based method was proposed to address low efficiency, high cost, and unstable accuracy in manual inspection on traditional media box production lines. The original ...