By Prof. Seungchul Lee
Industrial AI Lab at POSTECH
Table of Contents
1. Pre-trained Model (VGG16)
Training a model on ImageNet from scratch takes days or weeks.
Many models trained on ImageNet and their weights are publicly available!
Use pre-trained weights, remove last layers to compute representations of images
The network is used as a generic feature extractor
Train a classification model from these features on a new classification task
Pre- trained models can extract more general image features that can help identify edges, textures, shapes, and object composition
Better than handcrafted feature extraction on natural images