Overview: Clear problem definitions prevent wasted effort and keep machine learning work focused.Clean, well-understood data ...

Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...

While some AI courses focus purely on concepts, many beginner programs will touch on programming. Python is the go-to ...

Overview: In 2025, Java is expected to be a solid AI and machine-learning language.Best Java libraries for AI in 2025 can ease building neural networks, predict ...

Predicting earthquakes has long been an unattainable fantasy. Factors like odd animal behaviors that have historically been thought to forebode earthquakes are not supported by empirical evidence. As ...

Using mathematics in deep learning helps us understand which types of problems are most appropriate for ANNs, how to best structure the networks, how long they should train and can generally help ...

Objective: The aim of the present study proposed a deep learning framework for different influenza epidemic states based on Baidu index and the influenza-like-illness rate (ILI%). Methods: Official ...

Abstract: This research addresses the challenge of camera calibration and distortion parameter prediction from a single image using deep learning models. The main contributions of this work are: (1) ...

To address the issues of missed detection and false detection during the defect inspection process of the PCB, an improved YOLOv7-based algorithm for PCB defect detection is proposed. Firstly, the ...