276 citations · 375 across the 16 of their papers we have counts for
10 papers · 1 filter
Semi-Supervised Deep Learning for Abnormality Classification in Retinal Images
Bruno Lecouat, Ken Chang, Chuan-Sheng Foo +7
Supervised deep learning algorithms have enabled significant performance gains in medical image classification tasks. But these methods rely on large labeled datasets that require…
Adversarially Learned Anomaly Detection
Houssam Zenati, Manon Romain, Chuan Sheng Foo +2
Anomaly detection is a significant and hence well-studied problem. However, developing effective anomaly detection methods for complex and high-dimensional data remains a challenge…
Predicting thermoelectric properties from crystal graphs and material descriptors - first application for functional materials
Leo Laugier, Daniil Bash, Jose Recatala +5
We introduce the use of Crystal Graph Convolutional Neural Networks (CGCNN), Fully Connected Neural Networks (FCNN) and XGBoost to predict thermoelectric properties. The dataset fo…
Holistic Multi-modal Memory Network for Movie Question Answering
Anran Wang, Anh Tuan Luu, Chuan-Sheng Foo +3
Answering questions according to multi-modal context is a challenging problem as it requires a deep integration of different data sources. Existing approaches only employ partial i…
TEA-DNN: the Quest for Time-Energy-Accuracy Co-optimized Deep Neural Networks
Lile Cai, Anne-Maelle Barneche, Arthur Herbout +4
Embedded deep learning platforms have witnessed two simultaneous improvements. First, the accuracy of convolutional neural networks (CNNs) has been significantly improved through t…
Manifold regularization with GANs for semi-supervised learning
Bruno Lecouat, Chuan-Sheng Foo, Houssam Zenati +1
Generative Adversarial Networks are powerful generative models that are able to model the manifold of natural images. We leverage this property to perform manifold regularization b…