The rapid development of deep learning in recent years is largely due to the rapid increase in the scale of data. The availability of large amounts of data is revolutionary for model training by the ...

Recent advances in deep learning have significantly transformed mineral classification methodologies, supplanting labour‐intensive manual approaches with automated, high-precision systems. By ...

An international research team has developed a novel PV fault detection method based on deep learning of aerial images. The proposed methodology utilizes the convolutional neural network (CNN) ...

In traditional semiconductor packaging, manual defect review after automated optical inspection (AOI) is an arduous task for operators and engineers, involving review of both good and bad die. It is ...

Four research papers of the study were recently published in SCI-indexed journals, and its findings have been presented at ...

The Global Mapper Insight and Learning Engine™ (Beta) provides trained models for land cover classification, vehicle identification, and building extraction. This update to Global Mapper includes ...

In a recent article published in the journal Engineering, researchers presented a comprehensive review of the fast-growing ...

Deep Learning is probably the most popular form of machine learning at this time. Although not every problem boils down to a deep learning model, in domains such as computer vision and natural ...