25 citations · 108 across the 15 of their papers we have counts for
30 papers
Collaborative Multi-Teacher Knowledge Distillation for Learning Low Bit-width Deep Neural Networks
Cuong Pham, Tuan Hoang, Thanh-Toan Do
Knowledge distillation which learns a lightweight student model by distilling knowledge from a cumbersome teacher model is an attractive approach for learning compact deep neural n…
Vision Transformer Visualization: What Neurons Tell and How Neurons Behave?
Van-Anh Nguyen, Khanh Pham Dinh, Long Tung Vuong +4
Recently vision transformers (ViT) have been applied successfully for various tasks in computer vision. However, important questions such as why they work or how they behave still…
Logic Rules Meet Deep Learning: A Novel Approach for Ship Type Classification
Manolis Pitsikalis, Thanh-Toan Do, Alexei Lisitsa +1
The shipping industry is an important component of the global trade and economy, however in order to ensure law compliance and safety it needs to be monitored. In this paper, we pr…
Similarity of Classification Tasks
Cuong Nguyen, Thanh-Toan Do, Gustavo Carneiro
Recent advances in meta-learning has led to remarkable performances on several few-shot learning benchmarks. However, such success often ignores the similarity between training and…
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…