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Computer Vision
Chapters

1Foundations of Image Formation

2Low-Level Image Processing

3Feature Detection and Representation

4Classical Computer Vision: Geometry and Matching

5Machine Learning for Vision

6Deep Learning Foundations for Vision

7Advanced Deep Architectures and Vision Transformers

8Object Detection, Localization, and Recognition

Sliding Window and Classical DetectionRegion Proposal MethodsAnchor Boxes and Anchor-free ApproachesLoss Functions for DetectionNon-Maximum Suppression TechniquesMulti-scale and Context ModelingMulti-label and Fine-grained RecognitionTracking-by-Detection ConceptsEvaluation Metrics for DetectionPractical Detection System Design
Courses/Computer Vision/Object Detection, Localization, and Recognition

Object Detection, Localization, and Recognition

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Cover methods to detect and localize objects, multi-class recognition, anchor design, loss functions, and modern detection pipelines.

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7 of 10

Multi-label and Fine-grained Recognition

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