For decades, scientists have looked to light as a way to speed up computing. Photonic neural networks—systems that use light ...

This paper explores the use of deep learning to classify experimentally measured textured microstructures without knowledge of crystallographic orientation. A deep convolutional neural network is used ...

Learn about the most popular and effective statistical models for image classification and how they work. Compare logistic regression, KNN, SVM, decision trees, and neural networks.

By learning the relevant features of clinical images along with the relationships between them, the neural network can outperform more traditional methods.

Deep neural networks are at the heart of artificial intelligence, ranging from pattern recognition to large language and ...

Recent research has employed chemical reaction networks (CRNs), which harness biochemical processes for computations that translate interactions involving biochemical species into graphical form.

Existing three-dimensional (3D) neuronal culture technology has limitations in brain research due to the difficulty of ...

Over the past years, computer scientists have introduced increasingly sophisticated generative AI models that can produce ...

A Comparative Study of AI-Powered Chatbot for Health Care. Journal of Computer and Communications, 13, 48-66. doi: 10.4236/jcc.2025.137003 . The need for this research arises from the increasing ...

Many existing methods for exploring the link between neural activity and behavior rely on the analysis of static images and ... neural network architecture and training approach." The researchers ...

The agentic AI solution, known internally as Weave, launched alongside a model benchmarking tool called LLM-IQ. It was built from the ground up using data sourced from carriers and operators to create ...