This document discusses feature learning for image classification. It notes that computer vision is challenging and that machine learning algorithms require good feature representations of input data rather than raw pixels. The key question is whether machine learning can automatically learn good feature representations rather than relying on hand-tuned features designed by experts. The document then outlines using unsupervised feature learning to find better representations of images than raw pixels by using machine learning algorithms on unlabeled image data.

1. Feature learning for image classification Kai Yu and Andrew Ng

2. Computer vision is hard

3. Machine learning and feature representations Input Input space Learning algorithm pixel 1 Motorbikes “ Non”-Motorbikes pixel 1 pixel 2

4. Machine learning and feature representations Input Input space Feature space Feature representation Learning algorithm pixel 1 “ wheel” Motorbikes “ Non”-Motorbikes handle wheel

5. How is computer perception done? Object detection Audio classification Helicopter control Image Low-level vision features Recognition Image Grasp point Low-level features Low-level state features Action Helicopter Audio Low-level audio features Speaker identification

6. Learning representations Sensor Learning algorithm Feature Representation

7. Computer vision features SIFT Spin image HoG RIFT Textons GLOH

8. Audio features ZCR Spectrogram MFCC Rolloff Flux Problems of hand-tuned features 1. Needs expert knowledge 2. Time-consuming and expensive 3. Does not generalize to other domains

9. Computer vision is more than pictures Can we automatically learn good feature representations? Key question: Can we automatically learn a good feature representation? Camera array 3d range scan (laser scanner) 3d range scans (flash lidar) Audio Images Visible light image Thermal Infrared Thermal Infrared Video

10. Learning representations Sensor Learning algorithm Feature Representation

11. Sensor representation in the brain [BrainPort; Martinez et al; Roe et al.] Human echolocation (sonar) Auditory cortex learns to see. Auditory Cortex Seeing with your tongue

13. The goal of Unsupervised Feature Learning Unlabeled images Learning algorithm Feature representation