Capsule Networks tries to solve the limitations of CNNs by preserving information, using a routing algorithm.

Attention mechanisms enable models to focus on specific parts of input data, enhancing their ability to process sequences effectively.

YOLOX is a powerful object detection model, which introduced an anchor-less design and decoupled head. Learn how it works and its benefits!

This article explores computer vision trends and how advances in AI technology will impact industry, businesses, and society.

A comprehensive guide to help understand and lower the costs of computer vision. Strategies to save costs and power cost-efficient AI vision.

DETR is a method for object detection with transformers. Explore its architecture, how it predicts bounding boxes and labels, and use cases.

Our guide to Detectron2 dives into the framework's computer vision capabilities, covering everything from its architecture to use cases.

We deep dive into the foundations of deep learning with deep belief networks: their architecture, capabilities, applications and challenges.

Action localization identifies and localizes human actions within video sequences, making them searchable, analyzable, and more meaningful.

Precision vs. recall are two essential metrics to measure model performance. Learn how they work and how to use them in practical use cases.

From definition to implementation to tools, this guide offers a complete rundown on experiment tracking in machine learning.

A landmark ruling by the UK High Court set a new precedent for AI IP protection. Explore its implications and the challenges in AI patenting.