An Iterative Reconstruction Algorithm Based on Detail Transfer for Few-View Computed Tomography. Journal of Signal and ...

AI-powered biosensors can analyze intricate datasets from sensors in real time. Machine learning and deep learning algorithms ...

The MES system integrates genetic algorithms and particle swarm optimization mixed algorithms to capture over 10 types of ...

Personalized advertising remains one of the most data-intensive and dynamic challenges in modern e-commerce systems. A newly proposed AI framework tackles information overload in e-commerce platforms ...

New research indicates that AI models can get smarter at seeing by solving jigsaw puzzles. Rearranging scrambled images, ...

This FAQ explores the fundamental architecture of neural networks, the two-phase learning process that optimizes millions of ...

Soybean is one of the world’s major oil-bearing crops and occupies an important role in the daily diet of human beings. However, the frequent occurrence of soybean leaf diseases caused serious threats ...

The rapid escalation in tourist visitation poses significant challenges, including traffic congestion, overcapacity at scenic attractions, heightened risks of safety incidents, and diminished visitor ...

In this tutorial, we take a hands-on approach to building an advanced convolutional neural network for DNA sequence classification. We focus on simulating real biological tasks, such as promoter ...

1 Department of Mathematics and Statistics, Loyola University Chicago, Chicago, IL, USA. 2 Department of Mathematics and Computer Science, Islamic Azad University, Science and Research Branch, Tehran, ...

Abstract: The domain of Deep learning is an influential domain for performing the exhausting tasks like image recognition and classification. Researchers have raised different convolution neural ...