Search Results for author: Sheng Mei Shen

Found 3 papers, 1 papers with code

SB-MTL: Score-based Meta Transfer-Learning for Cross-Domain Few-Shot Learning

no code implementations3 Dec 2020 John Cai, Bill Cai, Sheng Mei Shen

Our method, called Score-based Meta Transfer-Learning (SB-MTL), combines transfer-learning and meta-learning by using a MAML-optimized feature encoder and a score-based Graph Neural Network.

cross-domain few-shot learning Domain Adaptation +1

Cross-Domain Few-Shot Learning with Meta Fine-Tuning

no code implementations21 May 2020 John Cai, Sheng Mei Shen

In our final results, we combine the novel method with the baseline method in a simple ensemble, and achieve an average accuracy of 73. 78% on the benchmark.

cross-domain few-shot learning Data Augmentation +2

Anomaly Detection with Adversarial Dual Autoencoders

2 code implementations arXiv.org 2019 Ha Son Vu, Daisuke Ueta, Kiyoshi Hashimoto, Kazuki Maeno, Sugiri Pranata, Sheng Mei Shen

Semi-supervised and unsupervised Generative Adversarial Networks (GAN)-based methods have been gaining popularity in anomaly detection task recently.

Anomaly Detection Image Generation

Cannot find the paper you are looking for? You can Submit a new open access paper.