New research offers clues to what goes on inside the minds of machines as they learn to see. Instead of attempting to account for a neural network's decision-making on a post hoc basis, their method ...

Overview A mix of beginner and advanced-level books to suit various learning needs.Each book blends theory with practical ...

Recent advancements have witnessed an impressive convergence between neural network architectures and spectroscopic techniques within computer vision. Deep learning methods, particularly convolutional ...

What are convolutional neural networks in deep learning? Convolutional neural networks are used in computer vision tasks, which employ convolutional layers to extract features from input data.

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 are ...

During my first semester as a computer science graduate student at Princeton, I took COS 402: Artificial Intelligence. Toward the end of the semester, there was a lecture about neural networks. This ...

Given computer vision’s place as the cornerstone of an increasing number of applications from ADAS to medical diagnosis and robotics, it is critical that its weak points be mitigated, such as the ...

Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. Welcome to the forefront of industrial innovation, where artificial intelligence, machine ...

DURHAM, N.C. -- The artificial intelligence behind self-driving cars, medical image analysis and other computer vision applications relies on what's called deep neural networks. Loosely modeled on the ...