Which Machine Learning Models Are Most Used In Crypto Signal Generation?

Machine learning is transforming how crypto traders create and understand signals. From supervised models such as Random Forests and Gradient Boosting Machines to sophisticated deep learning hybrids ...
Frontiers

Advancing Computational Material Science and Mechanics through Integrated Deep Learning Models

The field of computational materials science has been profoundly transformed by integrating deep learning and other machine learning methodologies. These sophisticated data-driven approaches have ...
Devdiscourse

How generative AI is driving the future of plant gene editing

Traditional breeding and genetic modification methods have struggled to keep pace with the rapid evolution of plant viruses. CRISPR/Cas systems, originally derived from bacterial immune responses, ...
Natural Science News

Improved image recognition helps identify different grape leaf varieties

Deep learning improves grape leaf variety identification, crucial for viticulture. Researchers optimized a DenseNet201 neural ...

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

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 ...

WiMi Studies Hybrid Quantum-Classical Convolutional Neural Network Model

BEIJING, Oct. 23, 2025––WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram ...
Scientific Research Publishing

Graph Neural Networks for Anomaly Detection in Cloud Infrastructure ()

Graph Neural Networks for Anomaly Detection in Cloud Infrastructure ...
Design And Reuse

Ceva Advancing Real-Time AI with Transformers and Intelligent Quantization

In an earlier collaborative project, Ceva worked with CERN on the trigger system of the Large Hadron Collider (LHC), a sophisticated real-time filtering mechanism that deals with the torrent of ...
University of Surrey

Xiaolong Han

Zehong Wang, Xiaolong Han, Yanru Chen, Xiaotong Ye, Keli Hu, Donghua Yu (2022) Prediction of willingness to pay for airline seat selection based on improved ensemble learning Airlines have launched ...
Devdiscourse

How AI integration in biosensors enhances food safety and accuracy

AI-powered biosensors can analyze intricate datasets from sensors in real time. Machine learning and deep learning algorithms ...
Frontiers

The design of multiple orthogonal signals based on auto-encoder optimization network

As an important part of active sonar, transmitted signals have a great influence on the performance of ocean exploration, however, in the actual environment, due to the existence of the Doppler ...
IEEE

Co-Design of Lightweight Neural Network and Low-Power Edge Computing Architecture for Intelligent Electronic Nose System

Abstract: The powerful feature extraction capabilities of deep learning can improve the recognition performance of the electronic nose system effectively. However, there is a conflict between the ...