Recurrent Neural Networks (RNN): A special type of neural network, RNN is a complex network that uses the output of a node ...

Generative AI is revolutionizing the field of cybersecurity by providing advanced tools for threat detection, analysis, and ...

MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, have developed a quantum algorithm technology for deep convolutional neural network (CNN) exchange ...

Deep neural networks (DNNs) have revolutionized machine learning, yet their success defies classical expectations. They ...

Abstract: Effective detection and classification of forest fire imagery are critical for timely and efficient wildfire management. Convolutional Neural Networks (CNNs) have demonstrated potential in ...

Each receives $2,000, and will compete for another $1.2 million. See all California students, their schools, and their ...

Morphological profiling allows accurate identification of cell types in dense iPSC-derived cultures, allowing its use for quality control and differentiation monitoring.

An Effective Cloud Detection Network for Remote Sensing Images. Journal of Computer and Communications, 13, 1-14. doi: 10.4236/jcc.2025.131001 . Optical remote sensing technology is increasingly ...

A groundbreaking study by researchers from the University of Namur, Belgium introduces a novel, contactless method for ...

Constrained deep learning is an advanced approach to training deep neural networks by incorporating domain-specific constraints into the learning process.

Then, based on G-PLIF, we designed a Multi-Scale-Residual Spiking Neural Network (MSR-SNN) specifically for the classification tasks of neuromorphic vision objects. The concept of a multi-scale ...

Successfully established a multiclass text classification model by fine-tuning pretrained DistilBERT transformer model to classify several distinct types of mental health statuses such as anxiety, ...