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 ...
EurekAlert!

Enhancing genomic prediction accuracy of swine agricultural economic traits in CNN models

Deep learning methods such as multilayer perceptrons (MLPs) and convolutional neural networks (CNNs) have been applied to predict the complex traits in animal and plant breeding. However, it remains ...
Scientific Research Publishing

Convolutional Homeomorphic Error-Correcting Codes Utilizing Nano Controlled-Selector Architectural Effectuation ()

1 Department of Computer Engineering, School of Engineering, The University of Jordan, Amman, Jordan. 2 Department of Data Science and Artificial Intelligence, Faculty of Information Technology, ...
IEEE

Deep Equilibrium Convolutional Sparse Coding for Hyperspectral Image Denoising

Abstract: Hyperspectral images (HSIs) play a crucial role in remote sensing but are often degraded by complex noise patterns. Ensuring the physical property of the denoised HSIs is vital for robust ...
GitHub

convolutional-sparse-coding

Experiments for ICML paper DICOD: Distributed Convolutional Coordinate Descent for Convolutional Sparse Coding, ICML 2018, T. Moreau, L. Oudre, N. Vayatis.
Frontiers

Convolutional neural networks decode finger movements in motor sequence learning from MEG data

1 Institute of Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia 2 Department of Learning, Data Analytics and Technology, Section Cognition, Data and ...
Frontiers

DTCNet: finger flexion decoding with three-dimensional ECoG data

School of Big Data, Zhuhai College of Science and Technology, Zhuhai, China ECoG signals are widely used in Brain-Computer Interfaces (BCIs) due to their high spatial resolution and superior signal ...
GitHub

QTS2D: Quantum-Based Image Encoding of Time Series

QTS2D is a Python library for encoding time series data into image representations using quantum computing principles. These image-based representations can then be used as input for various machine ...