Instance Segmentation
Combining object detection and segmentation to identify individual object instances at the pixel level.
Your route here
9 stops · basics first
- Machine Learning ✓ understood
Building systems that learn patterns from data instead of following hand-written rules, getting better at a task as they see more examples.
- Supervised Learning ✓ understood
Learning from examples paired with the correct answer, so a model can predict answers for new inputs it hasn't seen.
- Classification ✓ understood
A supervised learning task where the model assigns each input to one of a fixed set of categories, such as spam or not spam.
- Neural Network ✓ understood
A computational model inspired by biological neural networks, consisting of interconnected nodes (neurons) organized in layers that process information through weighted connections.
- Deep Learning ✓ understood
A subset of machine learning that uses neural networks with multiple layers (deep neural networks) to learn hierarchical representations of data.
- Computer Vision ✓ understood
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.
- Semantic Segmentation ✓ understood
Classifying every pixel in an image into categories, creating a pixel-level understanding of scenes.
- Bounding Box ✓ understood
A rectangular box defined by coordinates that localizes an object in an image, used in object detection.
- Object Detection ✓ understood
Finding every object of interest in an image and giving each a class label, a confidence score and a bounding box.
- Instance Segmentation · you are here ✓ understood