Deep convolutional neural networks (CNNs) have recently shown very high accuracy in a
wide range of cognitive tasks, and due to this, they have received significant interest from the …

Deep learning based on neural networks has been widely used in image recognition,
speech recognition, natural language processing, automatic driving, and other fields and …

Recent breakthroughs in recurrent deep neural networks with long short-term memory
(LSTM) units have led to major advances in artificial intelligence. However, state-of-the-art …

Many old oilfields have missed or distorted well logs data, which is due to long history of
shutdown, poor borehole conditions, damaged instrument, and other reasons. These bring …

Proteins mainly perform their functions by interacting with other proteins. Protein–protein
interactions underpin various biological activities such as metabolic cycles, signal …

In recent years, research in applying optimization approaches in the automatic design of
deep neural networks has become increasingly popular. Although various approaches have …

This paper aims to examine the role of global positioning system (GPS) sensor data in real-
life physical activity (PA) type detection. Thirty-three young participants wore devices …

Background Protein-protein interaction (PPI) is very important for many biochemical
processes. Therefore, accurate prediction of PPI can help us better understand the role of …

Ground motion target recognition based on seismic signals is more convenient and efficient
than traditional manual patrol identification. However, current high-precision identification …

Deep Neural Networks (DNNs) have achieved remarkable accuracy improvements for
automatic modulation classification. However, the employed networks often have millions of …