Convolutional neural network (CNN) hardware accelerators for specialized Internet of
Things (IoT) requiring high accuracy is an emerging research topic. The pooling module in a …

Neural networks have proven to be a highly effective tool for solving complex problems in
many areas of life. Recently, their importance and practical usability have further been …

Deep neural networks (DNNs) have become a relevant subject in the classification of radio
frequency signals and remote sensing data. A primary challenge is a tradeoff between …

In a conventional art course, it is important for a teacher to provide feedback and guidance to
individual students based on their learning status. However, it is challenging for teachers to …

For more than three decades, the part of the geoscientific community studying landslides
through data-driven models has focused on estimating where landslides may occur across a …

Taxonomic studies of leaves are one of the most effective means of correctly identifying plant
species. In this paper, mixed activation function is used to improve the ResNet50 network in …

Dysphagia is a common geriatric syndrome that might induce serious complications and
death. Standard diagnostics using the Videofluoroscopic Swallowing Study (VFSS) or …

In recent years, the rapid development of deep learning has led to a wide range of
applications in the field of medical image classification. The variants of neural network …

Recent developments reveal the prominence of Diabetic Retinopathy (DR) grading. In the
past few decades, Wavelet-based DR classification has shown successful impacts and the …

Background Deep Learning is an AI technology that trains computers to analyze data in an
approach similar to the human brain. Deep learning algorithms can find complex patterns in …