EurekAlert!

Transfer learning empowers material Z classification with muon tomography

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 ...

WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification

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

Decoding the shadows: Vehicle recognition software uncovers unusual traffic behavior

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

Hyperspectral Image Classification Based on Subgraph-Dependent Neural Network

Abstract: Hyperspectral image classification methods based on subgraph neural networks (SGNNs) are rarely explored, and its advantage is that it can alleviate the neighbor explosion problem. After ...
Frontiers

Self-supervised transfer learning for few-shot classification on marine plankton images

The following data augmentation (T) methods are used: 1) random cropping of the image with a scale ratio between 0.5 and 1.0, and then resizing it back to the original size using bilinear ...
IEEE

Application of Quantitative Interpretability to Evaluate CNN-Based Models for Medical Image Classification

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