AIL862: Difference between revisions
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| credits = 3 | | credits = 3 | ||
| credit_structure = 3-0-0 | | credit_structure = 3-0-0 | ||
| pre_requisites = COL333, COL671, COL774, or with instructor's | | pre_requisites = [[COL333]], [[COL671]], [[COL774]], or with instructor's | ||
| overlaps = | | overlaps = | ||
}} | }} | ||
== AIL862 : Special Topics in Computer Vision == | == AIL862 : Special Topics in Computer Vision == | ||
The course will focus on few specialized applications of computer vision such as mobility, transportation systems, healthcare, wellness, virtual and augmented reality, computational biology, genetics, etc. The course will discuss various computer vision techniques developed for problems in these domains. AIV790 Ethical Considerations in MINDS 1 Credit (1-0-0) permission. Introduction to ethical issues in AI: bias, fairness, transparency, reliability, accountability, job loss, privacy, human-aware AI. AI models to debias training data. Explainability in ML. Adversarial robustness. Federated learning. 349 | The course will focus on few specialized applications of computer vision such as mobility, transportation systems, healthcare, wellness, virtual and augmented reality, computational biology, genetics, etc. The course will discuss various computer vision techniques developed for problems in these domains. [[AIV790]] Ethical Considerations in MINDS 1 Credit (1-0-0) permission. Introduction to ethical issues in AI: bias, fairness, transparency, reliability, accountability, job loss, privacy, human-aware AI. AI models to debias training data. Explainability in ML. Adversarial robustness. Federated learning. 349 | ||
Latest revision as of 16:21, 14 April 2026
| AIL862 | |
|---|---|
| Special Topics in Computer Vision | |
| Credits | 3 |
| Structure | 3-0-0 |
| Pre-requisites | COL333, COL671, COL774, or with instructor's |
| Overlaps | |
AIL862 : Special Topics in Computer Vision
The course will focus on few specialized applications of computer vision such as mobility, transportation systems, healthcare, wellness, virtual and augmented reality, computational biology, genetics, etc. The course will discuss various computer vision techniques developed for problems in these domains. AIV790 Ethical Considerations in MINDS 1 Credit (1-0-0) permission. Introduction to ethical issues in AI: bias, fairness, transparency, reliability, accountability, job loss, privacy, human-aware AI. AI models to debias training data. Explainability in ML. Adversarial robustness. Federated learning. 349