Introduction to the Class |
Course Introduction |
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Human Vision |
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From World to Images |
Image Formation |
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Computer Vision: Algorithms and Applications. Chapter 2.1 |
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Edge Detection |
Edge Detection |
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Computer Vision: Algorithms and Applications. Chapter 7.2. |
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Deep Learning |
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Computer Vision: Algorithms and Applications. Chapters 5.3 and 5.4. |
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Delineation |
Delineation |
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Computer Vision: Algorithms and Applications. Chapters 7.3. |
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Level Set Methods: An Overview |
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Deformable Models for Cartographic Modeling |
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Segmentation |
Segmentation |
Image segmentation handouts |
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Computer Vision: Algorithms and Applications. Chapter 7.5. |
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Transformers in Natural Language Processing (NLP) |
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Texture |
Texture |
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The Discrete Fourier Transform: Bracewell, chapter 11. |
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Shape from Shading and Texture |
Shape from Shading |
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Shape from Texture |
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Computer Vision: Algorithms and Applications. Chapter 13.1. |
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Shape from Stereo |
Shape from Stereo |
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Computer Vision: Algorithms and Applications. Chapter 12. |
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Shape from Contours |
Shape from Contours |
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Nerfs |
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Exercise session 1 |
Exercise Session 1 |
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Exercise Session 1 with solutions |
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Python support material |
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Exercise session 2 |
Exercise session 2 |
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Exercise Session 2 Answers |
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Graded exercise 1 - mock sample |
GE1 2023 - solution |
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GE1 2023 |
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Exercise session 4 |
Exercise Session 4 |
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Exercise Session 5 |
Exercise Session 5 |
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Exercise Session 7 |
Exercise Session 7 |
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Mock Exam |
Mock Exam 2020 |
Please find attached the mock exam to assist you in preparing for the final exam. In the real exam there will be 32 multiple choice questions and a text question. Multiple choice questions can have one or more correct answers. We will provide the solution to the mock exam later.
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Mock Exam 2021 |
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Mock Exam Answers 2021 |
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