Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

Can deep learning catch chronic illness before symptoms show? This article explores how time-aware neural networks are reshaping early detection and care planning for conditions like diabetes and COPD ...

Machine learning and other modeling approaches could aid in forecasting the arrival of floating Sargassum rafts that clog ...

Pratyosh Desaraju secures German utility patents for AI systems that automate legacy system enhancement and detect ...

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 ...

Humanoid and Cognitive Robotics Laboratory, Department of Automatics, Biocybernetics, and Robotics, Jožef Stefan Institute, Ljubljana, Slovenia Collaboration between humans and robots is essential for ...

Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the ...

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 ...

Abstract: Identifying the emotions hidden in speech (SER) encounters difficulties in virtue of the subjective and variable nature of human emotions, along with limitations such as data dependency, ...

This project uses deep learning techniques to detect malware by analyzing file characteristics, byte sequences, and behavioral patterns. It employs Convolutional Neural Networks (CNNs) for image-based ...

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