Deep Learning

Edge Intelligence or Edge AI moves AI computing from the cloud to edge devices, where data is generated. This is a key to AI democratization.

Deep learning requires massive amounts of sensitive data. This drives the importance of privacy-preserving deep learning for computer vision.

Face blur methods support privacy-preserving deep learning. Face blurring has little impact on the accuracy of vision recognition models.

Vision Processing Unit (VPU) chips are optimized for inference with pre-trained deep learning models, powering computer vision applications.

Face detection is one of the most popular computer vision applications and has greatly benefitted from new deep learning methods.

Face recognition technologies greatly advanced with deep learning-based methods. Read an overview about deep face recognition technology, its applications, and challenges.

Learn about self-supervised learning: What it is, examples and methods for computer vision. Fewer labels and smaller samples as new standard?

Easy-to-understand guide about Deep Reinforcement Learning. How it works, examples, and real-world applications of AI based decision-making.

Easy to understand guide, explaining basic concepts of Mask R-CNN and how this convolutional neural network works.

Everything you need to know about YOLOv5. Why it is controversial and the differences of YOLOv5 to previous YOLO versions.