Deep transfer learning has emerged as a powerful paradigm in image classification, enabling models to leverage knowledge acquired from large, labelled datasets to perform effectively on new tasks with ...

In deep learning, a vast amount of training data is usually required. However, in practice, we often hit a wall where we cannot prepare such a large amount of data.This is where the technique called ...

An empirical evaluation of ten convolutional neural network architectures across three imaging modalities reveals that ...

A systematic benchmarking study demonstrates that DenseNet-121 paired with the Adam optimizer achieves exceptional diagnostic ...

Mingai Li, received her B.Sc. degree and M.Sc. degree from Daqing Petroleum Institute, Heilongjiang, China, in 1987 and 1990 respectively, and Ph.D. degree from Beijing University of Technology, ...