Intro to IoU, a key metric in computer vision. This guide covers the mathematical aspects, applications, challenges, and advancements.

Meta releases Llama 2, marking a significant leap toward better and safer LLMs. Read more to learn about all the exciting new developments.

Differences, advantages, and practical examples of supervised and unsupervised learning methods - Learn when to use which.

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

AI music and LLMs are reshaping the music industry. We'll explore this subject in a case study of Microsoft’s Muzic framework.

This blog introduces the core concepts of Reinforcement Learning, the integration with Deep Learning, and the diverse applications from gaming to real-world sectors like healthcare

How to evaluate models, measure model accuracy and performance, and how to different compare computer vision models effectively.

Everything you need to know about PyTorch vs. TensorFlow. The advantages, differences in performance, accuracy, and ease of use.

How Data Augmentation can improve the performance of your deep learning models and expand limited, small datasets.

Adversarial machine learning is a growing threat in AI. Various adversarial attacks are used against machine learning systems.

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

Vision Transformers (ViT) brought recent breakthroughs in Computer Vision achieving state-of-the-art accuracy with better efficiency.