https://github.com/agrover112/siamesenet-search
MNIST digits image similarity search by Indexing with Annoy and using trained embeddings from a Siamese Net with Triplet Loss .
Science Score: 10.0%
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Low similarity (4.8%) to scientific vocabulary
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MNIST digits image similarity search by Indexing with Annoy and using trained embeddings from a Siamese Net with Triplet Loss .
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README.md
SiameseNet-Search
Search can be performed in various ways and using various architectures. In the following repository embeddings are created by using an non-cnn base embedding model which is tuned using a Siamese Neural Net with Triplet Loss inspired from F. Schroff, D. Kalenichenko and J. Philbin, "FaceNet: A unified embedding for face recognition and clustering," 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Boston, MA, 2015, pp. 815-823. paper from Google , on 10K MNIST digits images from train-set.The trained model is used to create embeddings for entire train-set and then Indexed using Approx Nearest Neighbours being faster than K-NN. More like a prototype.
Embedding Space Visualized
PCA used for visualizing the embedding space of 10K images of different classes.
References
- https://arxiv.org/pdf/1503.03832.pdf
- http://www.cs.cmu.edu/~rsalakhu/papers/oneshot1.pdf
- http://yann.lecun.com/exdb/mnist/
- http://cseweb.ucsd.edu/~dasgupta/papers/rptree-stoc.pdf
- https://github.com/spotify/annoy
- https://github.com/PotatoSpudowski/S.I.D.E
Owner
- Login: Agrover112
- Kind: user
- Repositories: 113
- Profile: https://github.com/Agrover112
Humans trying to understand machines and people.
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