Hyderabad: Artificial Intelligence (AI) is transforming the way sleep disorders are diagnosed, with researchers at the ...
Learn With Jay on MSNOpinion
Supervised learning made easy: Real-world example explained
In this video, we will study Supervised Learning with Examples. We will also look at types of Supervised Learning and its ...
Bipolar Disorder, Digital Phenotyping, Multimodal Learning, Face/Voice/Phone, Mood Classification, Relapse Prediction, T-SNE, Ablation Share and Cite: de Filippis, R. and Al Foysal, A. (2025) ...
Forests and plantations play a vital role in carbon sequestration, yet accurately monitoring their growth remains costly and labor-intensive ...
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 ...
Fraud detection is defined by a structural imbalance that has long challenged data-driven systems. Fraudulent transactions typically account for a fraction of a percent of total transaction volume, ...
Abstract: Deep learning (DL) methods have been widely applied to synthetic aperture radar (SAR) land cover classification. The complexity of SAR data and the limited availability of labeled samples ...
Self-Supervised Learning with Adaptive Graph Modeling for EEG-Based Epileptic Seizure Classification
Abstract: Objective: Epileptic seizure classification using EEG signals remains a significant challenge due to complex spatial-temporal dependencies, limited labeled data, and severe class imbalance.
1 Center for Cyberspace Studies, Nasarawa State University, Keffi, Nigeria. 2 Department of Computer Engineering, Nile University of Nigeria, Abuja, Nigeria. 3 Department of Public and International ...
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