Social Image Systems: From Past to Present

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Edge Detection: Deep Learning Insights

Explores the evolution of edge detection techniques, from Canny to deep learning insights.

Transformers in Vision: Applications and Architectures

Covers the impact of transformers in computer vision, discussing their architecture, applications, and advancements in various tasks.

Transformers: Unifying Machine Learning Communities

Covers the role of Transformers in unifying various machine learning fields.

Convolutional Neural Networks

Introduces Convolutional Neural Networks, covering fully connected layers, convolutions, pooling, PyTorch translations, and applications like hand pose estimation and tubularity estimation.

Computer Vision: Recap

Recaps key concepts in computer vision, challenges, opportunities, and upcoming exam details.

Robust Vision: Data Augmentation and Ensembling Techniques

Explores data augmentation and ensembling techniques for robust vision, comparing ViT and ResNet models.

Convolutional Neural Networks

Introduces Convolutional Neural Networks (CNNs) for autonomous vehicles, covering architecture, applications, and regularization techniques.

Hand Pose Estimation

Covers hand pose estimation, regression techniques, and the evolution of image classification models from LeNet to VGG19.

Computer Vision: Image Formation and Transformation

Provides an overview of image formation and transformation principles in computer vision.

Shape from Shading: Recovering 3D Information from 2D Images

Covers the techniques for recovering 3D shape information from 2D images using shading models and modern deep learning approaches.