For people, matching what they see on the ground to a map is second nature. For computers, it has been a major challenge. A ...

Abstract: Deep neural networks have significantly improved the performance of low-level vision tasks but also increased the difficulty of interpretability. A deep understanding of deep models is ...

Abstract: Efficient large-scale monitoring of methane emissions is crucial for sustainable environmental management, necessitating advanced remote sensing techniques that process hyperspectral imagery ...

Saudi Arabia is not only making data centres, it is also using them. ALLAM, an Arabic-language AI model built with the Saudi ...

The Mixture of Experts (MoE) models are an emerging class of sparsely activated deep learning models that have sublinear compute costs with respect to their parameters. In contrast with dense models, ...

Pairing VL-PRMs trained with abstract reasoning problems results in strong generalization and reasoning performance improvements when used with strong vision-language models in test-time scaling ...

Classifying geospatial imagery remains a major bottleneck for applications such as disaster response and land-use monitoring-particularly in regions where annotated data is scarce or unavailable.

Learn what CNN is in deep learning, how they work, and why they power modern image recognition AI and computer vision programs.

Nvidia announced new infrastructure and AI models on Monday as it works to build the backbone technology for physical AI, including robots and autonomous vehicles that can perceive and interact with ...

AI training jobs offer flexible — and sometimes lucrative — side hustles. Major companies like Meta and OpenAI use data labelers to improve their chatbots' performance. Five people share why they like ...

Nov 27 (Reuters) - Top Chinese firms are training their artificial intelligence models abroad to access Nvidia's (NVDA.O), opens new tab chips and avoid U.S. measures aimed at curbing their progress ...