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Related lectures (32)

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Computer Vision History Recap

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

Document Segmentation: dhSegment

Explores the development and improvements of dhSegment, an open-source document segmentation package using PyTorch.

Learning Analytics: Classroom Analytics

Explores adaptive instruction, cognitive diagnosis, and handwriting difficulty analysis using machine learning models.

Image Recognition: Datasets and Algorithms

Explores a 2019 paper on image recognition, dataset challenges, biases, and the impact of large-scale datasets on deep learning models.

Self-Organization: Challenges and Applications

Explores the benefits, challenges, and applications of self-organization in various fields.

Visual Intelligence: Machines and Minds

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

Backpropagation and Neural Networks

Covers the backpropagation algorithm for training neural networks and the representation of functions in multilayer networks.

Deep Learning Fundamentals

Introduces the fundamentals of deep learning, covering neural networks, CNNs, special layers, weight initialization, data preprocessing, and regularization.

Visual Recognition: Integrated 3D + Semantics

Covers visual recognition models, scene graphs, neural networks, and embodied vision.

MaxPooling as inductive bias for images

Explores how MaxPooling enforces an inductive bias towards local translation invariance in convolutional neural networks.