2000222 / Few-shot-classification----Siamese-Networks-Triplet-LossLinks
Try to train a Triplet-Siamese-Netwrok with the constrained Triplet Loss for few shot image classification.
☆14Updated 5 years ago
Alternatives and similar repositories for Few-shot-classification----Siamese-Networks-Triplet-Loss
Users that are interested in Few-shot-classification----Siamese-Networks-Triplet-Loss are comparing it to the libraries listed below
Sorting:
- Code for research paper "Learning a Neural Network based Representation for Open Set Recognition" M. Hassen, P. K. Chan☆26Updated 5 years ago
- Codes for "Few-shot Image Classification: Just Use a Library of Pre-trained Feature Extractors and a Simple Classifier"☆32Updated 3 years ago
- Implementation for paper "Few-Shot Learning with Global Class Representations" (https://arxiv.org/abs/1908.05257)☆18Updated 2 years ago
- Pytorch implementation of four neural network based domain adaptation techniques: DeepCORAL, DDC, CDAN and CDAN+E. Evaluated on benchmark…☆91Updated 3 years ago
- Open-set Recognition with Adversarial Autoencoders☆38Updated 6 years ago
- Implementation of Domain Adaption in One-Shot Learning☆15Updated 6 years ago
- PyTorch code for our paper: Open Set Recognition Through Deep Neural Network Uncertainty: Does Out-of-Distribution Detection Require Gene…☆90Updated 3 years ago
- Pytorch implementation of the Trans paper "Few-shot Learning for Domain-specific Fine-grained Image Classification"☆27Updated 3 years ago
- ☆114Updated 4 years ago
- Multi-task learning for image classification implemented in PyTorch.☆99Updated 6 years ago
- A simple implementation of Deep Domain Confusion: Maximizing for Domain Invariance☆155Updated 6 years ago
- This is the PyTorch-0.4.0 implementation of few-shot learning on CIFAR-100 with graph neural networks (GNN)☆88Updated 6 years ago
- [AAAI 2021] Curriculum Labeling: Revisiting Pseudo-Labeling for Semi-Supervised Learning☆139Updated 4 years ago
- A Meta-Learning Approach for Few-Shot Anomaly Detection and One-Class Classification☆36Updated 3 years ago
- "Unified Deep Supervised Domain Adaptation and Generalization" (ICCV 2017)☆104Updated 5 years ago
- Simple Keras implementation of Triplet-Center Loss on the MNIST dataset☆45Updated 5 years ago
- A pytorch implementation of "Domain-Adaptive Few-Shot Learning"☆145Updated 4 years ago
- t-sne visualization of mnist images when feature is represented by raw pixels and cnn learned feature☆64Updated 7 years ago
- Tensorflow deep learning based domain adaptation model implementations with experiment of estimate MNIST by SVHN data (SVHN -> MNIST): DA…☆26Updated 6 years ago
- ICLR 2021: A Universal Representation Transformer Layer for Few-Shot Image Classification☆105Updated 4 years ago
- Keras implementation for the research paper "Towards Open Set Deep Networks" A Bendale, T Boult, CVPR 2016☆83Updated 2 years ago
- ☆23Updated 5 years ago
- Code for "Adversarial-Learned Loss for Domain Adaptation"(AAAI2020) in PyTorch.☆52Updated last year
- PyTorch implementation of "Self-Paced Balance Learning for Clinical Skin Disease Recognition"☆50Updated last year
- supervised and semi-supervised image classification with self-supervision (Keras)☆45Updated 4 years ago
- Deep domain adaptation networks (DDAN) library for Python with TensorFlow.☆72Updated 5 years ago
- Discriminative Feature Alignment for Unsupervised Domain Adaptation☆69Updated 4 years ago
- awesome few shot / meta learning papers☆53Updated 4 years ago
- ☆51Updated 10 years ago
- Code for 'Open Set Domain Adaptation by Backpropagation'☆75Updated 6 years ago