13 citations · 29 across the 22 of their papers we have counts for
9 papers · 1 filter
Reinforcement Learning in Financial Decision Making: A Systematic Review of Performance, Challenges, and Implementation Strategies
Mohammad Rezoanul Hoque, Md Meftahul Ferdaus, M. Kabir Hassan
Reinforcement learning (RL) is an innovative approach to financial decision making, offering specialized solutions to complex investment problems where traditional methods fail. Th…
A Comprehensive Review of Phase-Averaged and Phase-Resolving Wave Models for Coastal Modeling Applications
Md Meftahul Ferdaus, Nathan Alton Cooper, Austin B. Schmidt +4
Predicting ocean wave behavior is challenging due to the difficulty in choosing suitable numerical models among many with varying capabilities. This review examines the development…
Attention-Enhanced Prototypical Learning for Few-Shot Infrastructure Defect Segmentation
Christina Thrainer, Md Meftahul Ferdaus, Mahdi Abdelguerfi +4
Few-shot semantic segmentation is vital for deep learning-based infrastructure inspection applications, where labeled training examples are scarce and expensive. Although existing…
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…
KARMA: Efficient Structural Defect Segmentation via Kolmogorov-Arnold Representation Learning
Md Meftahul Ferdaus, Mahdi Abdelguerfi, Elias Ioup +3
Semantic segmentation of structural defects in civil infrastructure remains challenging due to variable defect appearances, harsh imaging conditions, and significant class imbalanc…
Foundation Models for Clean Energy Forecasting: A Comprehensive Review
Md Meftahul Ferdaus, Tanmoy Dam, Md Rasel Sarkar +2
As global energy systems transit to clean energy, accurate renewable generation and renewable demand forecasting is imperative for effective grid management. Foundation Models (FMs…
Few-Shot Learning in Video and 3D Object Detection: A Survey
Md Meftahul Ferdaus, Kendall N. Niles, Joe Tom +2
Few-shot learning (FSL) enables object detection models to recognize novel classes given only a few annotated examples, thereby reducing expensive manual data labeling. This survey…
FORTRESS: Function-composition Optimized Real-Time Resilient Structural Segmentation via Kolmogorov-Arnold Enhanced Spatial Attention Networks
Christina Thrainer, Md Meftahul Ferdaus, Mahdi Abdelguerfi +4
Automated structural defect segmentation in civil infrastructure faces a critical challenge: achieving high accuracy while maintaining computational efficiency for real-time deploy…