The ambiguity in medical imaging can present major challenges for clinicians who are trying to identify disease. For instance ...

MIT researchers made a technique that improves the trustworthiness of machine-learning models, which could help improve the accuracy and reliability of AI predictions for high-stakes settings such ...

The study establishes that advances in both sensor platforms and AI models have been instrumental in elevating crop type ...

Artificial Intelligence (AI) is rapidly transforming global maritime operations, ushering in a new era of automation, ...

Using machine learning, researchers automatically calibrate a comprehensive climate model, improving simulations of difficult features and taking steps toward more reliable climate projections.

Researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) have developed a novel artificial ...

In the ever-growing field of machine learning, one of the most significant challenges is making complex models interpretable and accessible. Enter AutoXplainAI, an innovative framework developed by ...

Roshan Kenia presented a poster on how AI-CNet3D enhances glaucoma classification using cross-attention networks while ...

Researchers from Nanjing University and Carnegie Mellon University have introduced an AI approach that improves how machines learn from past data—a process known as offline reinforcement learning.

In this article, author Jitender Jain discusses AI driven document processing techniques for an intelligent, adaptive ...

Training AI models used to mean billion-dollar data centers and massive infrastructure. Smaller players had no real path to ...

Check out our comprehsensive tutorial paper Foundations and Recent Trends in Multimodal Machine Learning: Principles, Challenges, and Open Questions. Tutorials on Multimodal Machine Learning at CVPR ...