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) ...
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Image SEO for multimodal AI
Images are now parsed like language. OCR, visual context and pixel-level quality shape how AI systems interpret and surface ...
Go fully offline with a private AI and RAG stack using n8n, Docker, Ollama, and Quadrant, so your personal, legal or medical files never leave your PC ...
Recent advancements in Graph Contrastive Learning (GCL) have demonstrated remarkable effectiveness in improving graph representations. However, relying on predefined augmentations (e.g., node dropping ...
Market-cap weighted crypto indexes underpin funds that hold huge slugs of bitcoin and ether, but plans for new ones could expand beyond the biggest and well-known coins. The latest comes from S&P ...
Hyperspectral images (HSIs) have very high dimensionality and typically lack sufficient labeled samples, which significantly challenges their processing and analysis. These challenges contribute to ...
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Nature’s Multi-Eyed Marvels: 16 Examples
Many people know that some animals have more than two eyes, but the variety and function of these extra eyes might surprise you. From reptiles with a hidden “third eye” that senses light, to insects ...
Graph neural networks in Alzheimer's disease diagnosis: a review of unimodal and multimodal advances
Alzheimer's Disease (AD), a leading neurodegenerative disorder, presents significant global health challenges. Advances in graph neural networks (GNNs) offer promising tools for analyzing multimodal ...
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