Computer vision

Machine learning

Comparative Analysis of Supervised and Self-Supervised Learning for Medical Imaging Datasets

Researchers from the University of Florence have conducted a comprehensive study on the performance of supervised learning (SL) and self-supervised learning (SSL) on small, imbalanced medical imaging datasets. The study, sponsored by NextGenerationEU, highlights the importance of carefully selecting learning paradigms based on specific application requirements. The findings indicate that

Machine learning

Efficient Convolutional Neural Networks Compression Using Reduced Storage Direct Tensor Ring Decomposition

Researchers at the Wroclaw University of Science and Technology in Poland have developed a novel method for compressing convolutional neural networks (CNNs) using reduced storage direct tensor ring decomposition (RSDTR). This approach offers improved efficiency, parameter compression rates, and FLOPS (floating-point operations per second) compression rates while maintaining high classification

Artificial intelligence

Qubrid AI Launches Startup Accelerator Program to Fuel Next-Generation AI Innovation

The Qubrid AI Startup Accelerator Program aims to empower early-stage and growth-stage AI startups with the necessary infrastructure, tools, and expertise to rapidly scale innovation. The program offers a comprehensive package of technical and business support, including GPU cloud credits, enterprise-grade infrastructure, flexible long-term GPU rentals, development tools, expert mentorship,

Artificial intelligence

Artificial Intelligence Research Yields New Insights on Machine Learning

Artificial intelligence research has been gaining significant momentum, with findings suggesting that deep vision models and quantum computing are revolutionizing computer vision. A recent report from Kyung Hee University in South Korea highlights the emergence of convolutional neural networks, vision transformers, and hybrid quantum-classical vision architectures. These advancements have shown