Researchers have demonstrated, for the first time, that transfer learning can significantly enhance material Z-class identification in muon tomography, even in scenarios with limited or completely ...

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...

Researchers at the Department of Energy's Oak Ridge National Laboratory have developed a deep learning algorithm that ...

Abstract: Convolutional Neural Networks (CNNs) dominate medical image classification, yet their “black box” nature limits understanding of their decision-making process. This study applies ...

Verizon said it has resolved an hours-long outage that is believed to have left tens of thousands of US customers without access to voice and data services for much of Wednesday. “Today, we let many ...

Organizations have a wealth of unstructured data that most AI models can’t yet read. Preparing and contextualizing this data is essential for moving from AI experiments to measurable results. In ...

Recently, there has been a lot of hullabaloo about the idea that large reasoning models (LRM) are unable to think. This is mostly due to a research article published by Apple, "The Illusion of ...

Develop an AI-based image classification system using CNN and transfer learning. The project includes data preprocessing, model training, fine-tuning, evaluation with precision, recall, and F1-score, ...

Learn how to build a fully connected, feedforward deep neural network from scratch in Python! This tutorial covers the theory, forward propagation, backpropagation, and coding step by step for a hands ...

An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy inefficiency in power amplifiers for next-generation wireless communication.