A research team at UCLA, led by Professor Aydogan Ozcan, has introduced BlurryScope, a compact, cost-effective scanning ...

In order to improve the diagnostic accuracy of deep-learning AI algorithms, models require larger amounts of high-quality ...

A study published in Molecules and led by researchers from the Changchun Institute of Optics, Fine Mechanics and Physics (CIOMP) of the Chinese Academy of Sciences demonstrated how deep learning can ...

Among deep learning techniques, convolutional neural networks are commonly used for image segmentation, detection, classification, and computer-aided diagnosis.

The software supports CNN, DNN and KNN algorithms. The use of CNN and DNN are currently mainstream in the development of deep learning (DL) for ADC classification in the semiconductor industry. We ...

The thesis not only showcases technical advancements but also underscores the importance of interpretability and scalability in agricultural AI solutions. Farmers and stakeholders are more likely to ...

Clinical Photographic Images: Deep learning algorithms such as DenseNet-169, ResNet-101, and EfficientNet-b4 have been employed to analyze clinical photographs of oral lesions.