To solve the problem of difficult quantitative identification of surface defect depth during laser ultrasonic inspection, a support vector machine-based method for quantitative identification of ...
Automated optical inspection (AOI) is a cornerstone in semiconductor manufacturing, assembly and testing facilities, and as such, it plays a crucial role in yield management and process control.
A lightweight cable-climbing robot with a computer vision system achieves 92% defect detection precision, enhancing safety ...
In a new proof-of-concept study researchers are pioneering the use of a unique Artificial Intelligence-based deep learning model as an assistive tool for the rapid and accurate reading of ultrasound ...
Active Learning to Reduce Data Requirements For Defect Identification in Semiconductor Manufacturing
A new technical paper titled “Exploring Active Learning for Semiconductor Defect Segmentation” was published by researchers at Agency for Science, Technology and Research (A*STAR) in Singapore. “We ...
Scientists from Tokyo Metropolitan University have used machine learning to automate the identification of defects in sister chromatid cohesion. They trained a convolutional neural network (CNN) with ...
Battery storage systems, and lithium-ion batteries in particular, are considered a key technology for the transport and energy transition. To meet the exponentially increasing demand for batteries and ...
A new classification of coronary congenital diseases is set to help surgeons identify secondary defects in the operating theater. Clinical cardiologists will also know what to look for on ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback