You Only Look Once - a real-time object detection architecture treating detection as regression.
Building systems that learn patterns from data instead of following hand-written rules, getting better at a task as they see more examples.
A computational model inspired by biological neural networks, consisting of interconnected nodes (neurons) organized in layers that process information through weighted connections.
A mathematical operation that applies filters/kernels to input data to extract features like edges, textures, and patterns.
A neural network that scans images with small learned filters, reusing the same weights at every position to build up from edges to whole objects.
A subset of machine learning that uses neural networks with multiple layers (deep neural networks) to learn hierarchical representations of data.
The field of AI that gets computers to extract meaning from images and video: what is in them, where it is, and how it moves.
A rectangular box defined by coordinates that localizes an object in an image, used in object detection.
Finding every object of interest in an image and giving each a class label, a confidence score and a bounding box.
You Only Look Once - a real-time object detection architecture treating detection as regression.
This concept is essential for understanding computer vision and forms a key part of modern AI systems.
Leads to
Nothing yet: a destination in its own right.