21 citations · 25 across the 9 of their papers we have counts for
9 papers
RoboGaze: Evaluating Robot World Models via Structured Vision-Language Analysis
Minh-Loi Nguyen, Nghiem T. Diep, Nghiem Tuong Diep +19
Robot world models now generate synthetic manipulation videos, but evaluating them is hard: realistic-looking outputs often violate physical laws, temporal consistency or task logi…
Self-Improving VLA Policies: Selected Diffusion Noise for Spurious-Robust Action Smoothing
Duc Minh Nguyen, Bao-Ngoc Dao, Tung M. Luu +15
Diffusion-based Vision-Language-Action (VLA) policies enable strong generalization in robotic manipulation, but remain sensitive to spurious visual correlations and noisy action ge…
Safety-Oriented Evaluation of Language Understanding Systems for Air Traffic Control
Yujing Chang, Yash Guleria, Duc-Thinh Pham +4
Air Traffic Control (ATC) is a safety-critical domain in which incorrect interpretation of instructions may lead to severe operational consequences. While large language models (LL…
Enhancing Few-Shot Classification of Benchmark and Disaster Imagery with ABHFA-Net
Gao Yu Lee, Tanmoy Dam, Md Meftahul Ferdaus +2
The rising incidence of natural and human-induced disasters necessitates robust visual recognition systems capable of operating under limited labeled data conditions. However, disa…
ANROT-HELANet: Adverserially and Naturally Robust Attention-Based Aggregation Network via The Hellinger Distance for Few-Shot Classification
Gao Yu Lee, Tanmoy Dam, Md Meftahul Ferdaus +2
Few-Shot Learning (FSL), which involves learning to generalize using only a few data samples, has demonstrated promising and superior performances to ordinary CNN methods. While Ba…
DRACO-DehazeNet: An Efficient Image Dehazing Network Combining Detail Recovery and a Novel Contrastive Learning Paradigm
Gao Yu Lee, Tanmoy Dam, Md Meftahul Ferdaus +2
Image dehazing is crucial for clarifying images obscured by haze or fog, but current learning-based approaches is dependent on large volumes of training data and hence consumed sig…
Dehazing Remote Sensing and UAV Imagery: A Review of Deep Learning, Prior-based, and Hybrid Approaches
Gao Yu Lee, Jinkuan Chen, Tanmoy Dam +3
High-quality images are crucial in remote sensing and UAV applications, but atmospheric haze can severely degrade image quality, making image dehazing a critical research area. Sin…
Unlocking the capabilities of explainable fewshot learning in remote sensing
Gao Yu Lee, Tanmoy Dam, Md Meftahul Ferdaus +2
Recent advancements have significantly improved the efficiency and effectiveness of deep learning methods for imagebased remote sensing tasks. However, the requirement for large am…
WATT-EffNet: A Lightweight and Accurate Model for Classifying Aerial Disaster Images
Gao Yu Lee, Tanmoy Dam, Md Meftahul Ferdaus +2
Incorporating deep learning (DL) classification models into unmanned aerial vehicles (UAVs) can significantly augment search-and-rescue operations and disaster management efforts.…