EurekAlert!

Using multimodal deep learning to detect malicious traffic with noisy labels

The success of a deep learning-based network intrusion detection systems (NIDS) relies on large-scale, labeled, realistic traffic. However, automated labeling of realistic traffic, such as by sand-box ...
News Medical

COMET model enhances disease prediction with deep learning

COMET, a novel machine learning framework, integrates EHR data and omics analyses using transfer learning, significantly enhancing predictive modeling and uncovering biological insights from small ...
AlphaGalileo

PlantIF: Revolutionizing plant disease diagnosis with multimodal learning for precision agriculture

A research team has developed a new model, PlantIF, that addresses one of the most pressing challenges in agriculture: the ...
Scientific Research Publishing

Applying Deep Learning Techniques for Automated Analysis and Interpretation of Financial Statements ()

Multimodal Learning, Deep Learning, Financial Statement Analysis, LSTM, FinBERT, Financial Text Mining, Automated Interpretation, Financial Analytics Share and Cite: Wandwi, G. and Mbekomize, C. (2025 ...
Scientific Research Publishing

Multimodal Digital Phenotyping for Bipolar Disorder: Robust Mood-State Classification and Early Relapse Risk Monitoring ()

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) ...
TechRadar

What is multimodal AI and why should we care about it?

When you purchase through links on our site, we may earn an affiliate commission. Here’s how it works. Picture a world where your devices don’t just chat but also pick up on your vibes, read your ...