Convolutional neural networks have been verified to be exceptionally powerful on extracting semantic features, which contribute to a great progress in computer vision. However, focusing too much on ...

The network trained on ImageNet classifies images into 1000 object categories, such as keyboard, mouse, pencil, and many animals.The main idea of the Inception module is that of running multiple ...

In this paper, the problem of image enhancement in the form of single image superresolution and compression artifact reduction is addressed by proposing a convolutional neural network with an ...

Recent advances in deep convolutional neural network (DCNN) provide an ideal test platform to examine the impact of visual experiences on face modules without genetic predisposition. DCNNs are found ...

Keywords: breast cancer, medical imaging, deep learning, convolutional neural networks, transfer learning. Citation: Das HS, Das A, Neog A, Mallik S, Bora K and Zhao Z (2023) Breast cancer detection: ...

In 2019, Pham and Whu predicted missing acoustic logging data by using a bidirectional convolutional long short-term memory network, and experimental results showed that the method had high accuracy.