A new study titled "An Efficient Method for Early Alzheimer’s Disease Detection Based on MRI Images Using Deep Convolutional ...

Researchers from the USC Viterbi School of Engineering are presenting 24 papers at the 2025 International Conference on Learning Representations (ICLR), Apr. 24-28, one of the premier global ...

The study demonstrates that AI can markedly enhance diagnostic accuracy in 2D mammographic screening, a method long regarded ...

Machine learning algorithms have played ... learning (a modified DenseNet) for classification. The system was implemented at Magori Polyclinic in Niamey, diagnosing breast cancer into normal and ...

The implementation of Machine Learning (ML ... Gaussian noise feature data augmentation. The Fine KNN algorithm provides the 93.4% and 92.3% classification accuracies of binary and multi-class ...

A data-driven approach can retire the endless, unproductive battles over race- and class-based affirmative action.

Furthermore, the proposed system outperforms conventional machine learning, deep learning, and transfer learning techniques. In addition to classification, the system accurately estimates tumor size, ...

learning. These kids, though, seem more jubilant than might be expected for a Tuesday morning in April. The days of dodging class or suffering from a lack of motivation appear to be a thing of the ...

SYDNEY: Australian and Canadian researchers have developed a cutting-edge machine learning algorithm capable of rapidly identifying heart disease and fracture risks using routine bone density scans.

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 ...

Includes comprehensive documentation and Jupyter notebooks. This project leverages deep learning to identify crop diseases from images. Built with TensorFlow, the app allows users to upload crop ...

A basic form of this often used for A/B testing is Thompson Sampling for solving Multi-Armed Bandit (MAB) problems where probability distributions and decision making are combined in the simplest way.