Computer vision continues to be one of the most dynamic and impactful fields in artificial intelligence. Thanks to breakthroughs in deep learning, architecture design and data efficiency, machines ...

In contrast, a traditional machine learning flow would fail. We can attribute deep learning advancements in computer vision to the massive amount of image data we have today.

Researchers at The University of Osaka have developed a computer graphics (CG) model, NeuraLeaf, capable of representing a ...

Complemented by deep learning, machine vision solutions have become a powerful tool for enhancing automated inspection capabilities.

Designed for edge devices and optimized to reduce latency and memory footprint, Syntiant’s hardware-agnostic deep learning models can be used for multiple vision-based applications such as object ...

Deep learning has shown amazing performance in various tasks, whether it be text, time series or computer vision. The success of deep learning comes primarily from the availability of large data ...

PyTorch 1.10 is production ready, with a rich ecosystem of tools and libraries for deep learning, computer vision, natural language processing, and more. Here's how to get started with PyTorch.

Recent studies have focused on integrating deep learning with computer vision to tackle the inherent challenges posed by the variable geometry and visual complexity of eggshell surfaces.

A scientific review of solar forecasting with computer vision and deep-learning tech identifies areas for improvement and calls for more collaboration between project developers and grid operators.