WiMi Studies Quantum Hybrid Neural Network Model to Empower Intelligent Image Classification

WiMi Studies Quantum Hybrid Neural Network Model to Empower Intelligent Image Classification BEIJING, Jan. 15, 2026––WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global ...
IEEE

MC-NCLWO: Newton’s Cooling Law-Based Oversampling Algorithm for Multi-Class Imbalanced Datasets With Feature Noise

Abstract: Imbalanced data classification remains a fundamental challenge in machine learning, especially in multi-class scenarios where feature noise, class overlap, and small disjunct sub-concepts ...
Scientific Research Publishing

Deb, K. (2011) Multi-Objective Optimisation Using Evolutionary Algorithms: An Introduction. In: Wang, L.H., Ng, A.H.C. and Deb, K., Eds., Multi-Objective Evolutionary ...

ABSTRACT: Multi-objective optimization remains a significant and realistic problem in engineering. A trade-off among conflicting objectives subject to equality and inequality constraints is known as ...
ccr-mag

MicroCloud Hologram Unveils Hybrid Quantum-Classical Breakthrough

MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the “Company”), a technology service provider, proposed a Quantum Convolutional Neural Network (QCNN) based on hybrid quantum-classical learning and ...
TMCnet

MicroCloud Hologram Inc. Releases Hybrid Quantum-Classical Convolutional Neural Network, Achieving New Breakthrough in MNIST Multi-Class Classification

SHENZHEN, China, Oct. 24, 2025 (GLOBE NEWSWIRE) -- MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the "Company"), a technology service provider, proposed a Quantum Convolutional Neural Network ...
Frontiers

A dynamic multitask evolutionary algorithm for high-dimensional feature selection based on multi-indicator task construction and elite competition learning

High-dimensional data often contain noisy and redundant features, posing challenges for accurate and efficient feature selection. To address this, a dynamic multitask learning framework is proposed, ...
IEEE

A Survey on Class Imbalance Learning Algorithms in Complex Scenarios

Abstract: Class imbalance introduces bias into model learning and remains a persistent and fundamental challenge in machine learning. When class imbalance is coupled with complex data distribution ...