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Siamese and triplet learning

Siamese and triplet networks with online triplet mining in PyTorch

Siamese and triplet learning is a PyTorch implementation of Siamese and triplet neural network architectures designed for learning embedding representations in machine learning tasks. These types of networks learn to map images into a compact feature space where the distance between vectors reflects the similarity between inputs. Such embeddings are commonly used in applications like face recognition, image similarity search, and few-shot learning.

Downloads: 1 This Week

Last Update: 2026-03-15
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