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Related lectures (32)

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Clustering: K-means & LDA

Covers clustering using K-means and LDA, PCA, K-means properties, Fisher LDA, and spectral clustering.

Visual Intelligence: Machines and Minds

Explores visual intelligence, covering image formation, perception, computer vision, correspondence learning, motion analysis, and recognition in videos.

Segmentation: Techniques and Applications

Explores segmentation techniques, including CNNs and U-Net models, for image recognition and analysis, emphasizing time-saving automated methods.

Annual Meeting Awards

Announces the winners of annual meeting awards, recognizing outstanding poster and video works, and pitches from the Next Tech program.

Recent Biometrics

Explores the basics, benefits, risks, and global impact of recent biometrics technology.

Modern Convolutional Networks and Image Recognition

Explores the evolution of deep convolutional networks and their impact on image recognition accuracy.

Visual Intelligence: Machines and Minds

Explores visual intelligence, image formation, computer vision, and representation understanding in machines and minds.

Deep Learning: No Free Lunch Theorem and Inductive Bias

Covers the No Free Lunch Theorem and the role of inductive bias in deep learning and reinforcement learning.

Deep Learning: Convolutional Neural Networks and Training Techniques

Discusses convolutional neural networks, their architecture, training techniques, and challenges like adversarial examples in deep learning.

Computer Vision History Recap

Offers a historical overview of computer vision, exploring key developments and influential figures in the field.