4 papers
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…
SaViD: Spectravista Aesthetic Vision Integration for Robust and Discerning 3D Object Detection in Challenging Environments
Tanmoy Dam, Sanjay Bhargav Dharavath, Sameer Alam +4
The fusion of LiDAR and camera sensors has demonstrated significant effectiveness in achieving accurate detection for short-range tasks in autonomous driving. However, this fusion…
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…