COVID-19 is an ongoing pandemic disease. To make more accurate diagnosis on COVID-
19 than existing approaches, this paper proposed a novel method combining DenseNet and …

The alarming rise in the ocean noises due to the ram** up of anthropogenic activities had
adversely impacted the marine fauna and altered the soundscape of the oceans. In recent …

Bacterial pathogens especially antibiotic-resistant ones are a public health concern
worldwide. To oppose the morbidity and mortality associated with them, it is critical to select …

Convolutional neural networks (CNNs) have achieved great success in image classification
tasks. In the process of a convolutional operation, a larger input area can capture more …

Music source separation has traditionally followed the encoder-decoder paradigm (eg,
hourglass, U-Net, DeconvNet, SegNet) to isolate individual music components from …

Music source separation is one of the old and challenging problems in music information
retrieval society. Improvements in deep learning lead to big progress in decomposing music …

This work improves a LeNet model algorithm based on a signal's bispectral features to
recognize the communication behaviors of a non-collaborative short-wave radio station. At …

The application of noninvasive methods to enhance healthcare systems has been facilitated
by the development of new technology. Among the four major cardiovascular diseases …

During the height of the COVID-19 pandemic, classical musicians had to find virtual
alternatives for reaching their audiences after canceling recitals and concert seasons. Social …

Herein, we proposed a multi-scale multi-band dilated time-frequency densely connected
convolutional network (DenseNet) with long short-term memory (LSTM) for audio source …