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About CS-671: Deep Learning and Its Applications Distance Metric Learning
This document summarizes a lecture on distance metric learning and siamese networks. It discusses how siamese networks can be used to learn a similarity metric for matching pairs of images by using a shared CNN to encode each image, calculating the distance between encodings, and optimizing a contrastive loss on positive and negative image pairs. Specifically, it uses Euclidean distance for positive pairs and hinge loss for negative pairs to learn image embeddings that bring similar images together and separate different images by a margin. The siamese network architecture can be varied for different tasks based on empirical performance.
Detailed Information
| Author: | ['Shashi Kumar Fagna'] |
|---|---|
| Publication Year: | 2020 |
| Pages: | 15 |
| Language: | English |
| Format: | |
| Price: | FREE |
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