This is the Windows app named Siamese and triplet learning whose latest release can be downloaded as siamese-triplettorch-0.3.1sourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
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Siamese and triplet learning
DESCRIPTION
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. The repository demonstrates how to train these models using contrastive loss and triplet loss functions, which encourage embeddings of similar samples to be close while pushing dissimilar samples farther apart. It includes data loaders, training scripts, neural network architectures, and evaluation metrics that allow researchers to experiment with different embedding learning strategies. The project also implements online pair and triplet mining techniques to efficiently generate training examples during model training.
Features
- PyTorch implementation of Siamese and triplet neural network architectures
- Embedding learning framework for similarity-based machine learning tasks
- Contrastive loss and triplet loss implementations for training models
- Dataset utilities that generate positive and negative pairs or triplets
- Online pair and triplet mining strategies for efficient training
- Example experiments using datasets such as MNIST and Fashion-MNIST
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/siamese-and-triplet.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
