Completed
Images are Numbers
Class Central Classrooms beta
YouTube videos curated by Class Central.
Classroom Contents
Convolutional Neural Networks
Automatically move to the next video in the Classroom when playback concludes
- 1 Intro
- 2 Images are Numbers
- 3 Tasks in Computer Vision
- 4 High Level Feature Detection
- 5 Manual Feature Extraction
- 6 Learning Feature Representations
- 7 Fully Connected Neural Network
- 8 Using Spatial Structure
- 9 Applying Filters to Extract Features
- 10 Feature Extraction with Convolution
- 11 Filters to Detect X Features
- 12 The Convolution Operation
- 13 Producing Feature Maps
- 14 Convolutional Layers: Local Connectivity
- 15 Introducing Non-Linearity
- 16 Pooling
- 17 CNNs for Classification: Feature Learning
- 18 CNNs for Classification: Class Probabilities
- 19 CNNs: Training with Backpropagation
- 20 ImageNet Dataset
- 21 ImageNet Challenge: Classification Task
- 22 An Architecture for Many Applications
- 23 Beyond Classification
- 24 Semantic Segmentation: FCNs
- 25 Driving Scene Segmentation
- 26 Image Captioning using RNNS
- 27 Impact: Face Detection
- 28 Impact: Self-Driving Cars
- 29 Impact: Healthcare
- 30 Deep Learning for Computer Vision: Summary
