AI in medical imaging market growth is driven by deep learning advancements, personalized medicine, lack of radiologists, and AI integration in telemedicine. It faces challenges like high costs, data ...

Analysis conducted by the Internet Watch Foundation (IWF) found that last year was the worst on record for AI-generated child ...

US researchers solve partial differential equations with neuromorphic hardware, taking us closer to world's first ...

Recent advances in computer vision and other types of artificial intelligence offer an opportunity for facial recognition to apply to bears and other animals.

ABSTRACT: Lung cancer is a deadly disease, but there is a big chance for the patient to be cured if he or she is correctly diagnosed in early stage of his or her case. At a first glance, lung X-ray ...

Since 2021, Korean researchers have been providing a simple software development framework to users with relatively limited AI expertise in industrial fields such as factories, medical, and ...

Abstract: Over the past few decades, convolutional neural network (CNN) has found broad applications in image recognition. Nevertheless, the operational environment of CNN is facing significant ...

When Fei-Fei Li arrived in Princeton in January 2007 as an assistant professor, she was assigned an office on the second floor of the computer science building. Her neighbor was Christiane Fellbaum.

Abstract: In this paper, an innovative Quantum image recognition algorithm, Quantum Auto Gradient Descent (QAGD), is proposed. The algorithm combines the advantages of quantum convolutional neural ...

Introduction: The state monitoring of tobacco leaves during the curing process is crucial for process control and automation of tobacco agricultural production. While most of the existing research on ...

With technological advancements and increasing user demands, human action recognition plays a pivotal role in the field of human-computer interaction. Among various sensing devices, WiFi equipment has ...