8 citations · 14 across the 3 of their papers we have counts for
5 papers
Multiple Meta-model Quantifying for Medical Visual Question Answering
Tuong Do, Binh X. Nguyen, Erman Tjiputra +3
Transfer learning is an important step to extract meaningful features and overcome the data limitation in the medical Visual Question Answering (VQA) task. However, most of the exi…
Graph-based Person Signature for Person Re-Identifications
Binh X. Nguyen, Binh D. Nguyen, Tuong Do +3
The task of person re-identification (ReID) is to match images of the same person over multiple non-overlapping camera views. Due to the variations in visual factors, previous work…
Multiple interaction learning with question-type prior knowledge for constraining answer search space in visual question answering
Tuong Do, Binh X. Nguyen, Huy Tran +3
Different approaches have been proposed to Visual Question Answering (VQA). However, few works are aware of the behaviors of varying joint modality methods over question type prior…
Deep Metric Learning Meets Deep Clustering: An Novel Unsupervised Approach for Feature Embedding
Binh X. Nguyen, Binh D. Nguyen, Gustavo Carneiro +3
Unsupervised Deep Distance Metric Learning (UDML) aims to learn sample similarities in the embedding space from an unlabeled dataset. Traditional UDML methods usually use the tripl…
Overcoming Data Limitation in Medical Visual Question Answering
Binh D. Nguyen, Thanh-Toan Do, Binh X. Nguyen +3
Traditional approaches for Visual Question Answering (VQA) require large amount of labeled data for training. Unfortunately, such large scale data is usually not available for medi…