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Computer Vision: History Recap & Logistics
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Related lectures (31)
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Neuro-symbolic Representations: Commonsense Knowledge & Reasoning
Delves into neuro-symbolic representations for commonsense knowledge and reasoning in natural language processing applications.
Neuro-symbolic Representations: Commonsense Knowledge & Reasoning
Explores neuro-symbolic representations for understanding commonsense knowledge and reasoning, emphasizing the challenges and limitations of deep learning in natural language processing.
Search Algorithms: Abductive Reasoning
Explores abductive reasoning, search algorithms, and heuristic search for problem-solving.
Machine Learning for Feature Extraction
Explores machine learning for feature extraction, 3D vision, and neural networks in mobile robotics.
Uncertain Reasoning: Bayesian Networks
Explores uncertain reasoning, Bayesian networks, and stochastic resolution, emphasizing the importance of probabilistic logic and abduction.
Computer Vision: Historical Insights and Project Inspirations
Explores the historical development of computer vision and inspires innovative project ideas.
Counterexample to Induction Theorem
Explores a counterexample to the induction principle, demonstrating a property of natural numbers.
Search Algorithms: Abductive Reasoning
Covers search algorithms, focusing on abductive reasoning and heuristic search strategies.
Logical Reasoning: Quiz Analysis
Analyzes a quiz on logical reasoning, discussing correct and incorrect answers.
Programming Thymio with VPL
Explores using VPL to program Thymio robots and addresses students' and teachers' challenges in programming.
