6 papers
KIGNet: Physics-Motivated Multi-Graph Representation Learning for Explainable Jet Tagging
Md Raqibul Islam, Adrita Khan, Mir Sazzat Hossain +6
Jet identification plays a central role in analyzing data from high-energy collider experiments. While deep learning has improved jet classification, it often lacks interpretabilit…
FedPoisonTTP: A Threat Model and Poisoning Attack for Federated Test-Time Personalization
Md Akil Raihan Iftee, Syed Md. Ahnaf Hasan, Amin Ahsan Ali +3
Test-time personalization in federated learning enables models at clients to adjust online to local domain shifts, enhancing robustness and personalization in deployment. Yet, exis…
pFedBBN: A Personalized Federated Test-Time Adaptation with Balanced Batch Normalization for Class-Imbalanced Data
Md Akil Raihan Iftee, Syed Md. Ahnaf Hasan, Mir Sazzat Hossain +5
Test-time adaptation (TTA) in federated learning (FL) is crucial for handling unseen data distributions across clients, particularly when faced with domain shifts and skewed class…
BD Open LULC Map: High-resolution land use land cover mapping & benchmarking for urban development in Dhaka, Bangladesh
Mir Sazzat Hossain, Ovi Paul, Md Akil Raihan Iftee +7
Land Use Land Cover (LULC) mapping using deep learning significantly enhances the reliability of LULC classification, aiding in understanding geography, socioeconomic conditions, p…
RGC-Bent: A Novel Dataset for Bent Radio Galaxy Classification
Mir Sazzat Hossain, Khan Muhammad Bin Asad, Payaswini Saikia +7
We introduce a novel machine learning dataset tailored for the classification of bent radio active galactic nuclei (AGN) in astronomical observations. Bent radio AGN, distinguished…
FedCTTA: A Collaborative Approach to Continual Test-Time Adaptation in Federated Learning
Rakibul Hasan Rajib, Md Akil Raihan Iftee, Mir Sazzat Hossain +4
Federated Learning (FL) enables collaborative model training across distributed clients without sharing raw data, making it ideal for privacy-sensitive applications. However, FL mo…