The human brain is often compared to a computer, but the latest wave of research shows it is closer to a self-building city, ...
ABSTRACT: This paper proposes a hybrid AI framework that integrates technical indicators, fundamental data, and financial news sentiment into a stacked ensemble learning model. The ensemble combines ...
CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...
When Edsger W. Dijkstra published his algorithm in 1959, computer networks were barely a thing. The algorithm in question found the shortest path between any two nodes on a graph, with a variant ...
Total Organic Carbon (TOC) is a fundamental parameter for evaluating source rock quality, yet the strong heterogeneity of the Qiongzhusi Formation shale reservoir in the Sichuan Basin severely limits ...
Abstract: Haze reduces visibility, hindering real-time image processing applications. Although deep learning-based dehazing algorithms can significantly enhance image quality, their high computational ...
VFF-Net introduces three new methodologies: label-wise noise labelling (LWNL), cosine similarity-based contrastive loss (CSCL), and layer grouping (LG), addressing the challenges of applying a forward ...
A group of researchers have developed an algorithm designed to prevent threat actors from disrupting quantum communication channels across an entire network. Researchers from Italy's Politecnico di ...
Artificial neural networks are machine learning models that have been applied to various genomic problems, with the ability to learn non-linear relationships and model high-dimensional data. These ...