Abstract: Convolutional Neural Networks (CNNs) are extensively utilized for image classification due to their ability to exploit data correlations effectively. However, traditional CNNs encounter ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

Accurate joint kinematics estimation is essential for understanding human movement and supporting biomechanical applications. Although optical motion capture systems are accurate, their high cost, ...

Pull requests help you collaborate on code with other people. As pull requests are created, they’ll appear here in a searchable and filterable list. To get started, you should create a pull request.

Abstract: A lightweight Convolutional Neural Network (CNN) has become one of the major studies in machine learning field to optimize its potential for employing it on the resource-constrained devices.

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In recent AI-driven disease diagnosis, the success of models has depended mainly on ...

Pull requests help you collaborate on code with other people. As pull requests are created, they’ll appear here in a searchable and filterable list. To get started, you should create a pull request.

Reliable estimation of Chlorophyll-a concentration (Chl-a) from remotely sensed data is essential for monitoring the health of aquatic ecosystems and supporting environmental policy decisions (El ...

The Bureau of Labor Statistics is reducing or ending the collection of data that is used to calculate the Consumer Price Index. By Ben Casselman Federal Reserve policymakers have stressed that their ...