6 citations · 15 across the 12 of their papers we have counts for
5 papers · 1 filter
Agentic AI as a Network Control-Plane Intelligence Layer for Federated Learning over 6G
Loc X. Nguyen, Ji Su Yoon, Huy Q. Le +6
The shift toward user-customized on-device learning places new demands on wireless systems: models must be trained on diverse, distributed data while meeting strict latency, bandwi…
FedFeat+: A Robust Federated Learning Framework Through Federated Aggregation and Differentially Private Feature-Based Classifier Retraining
Mrityunjoy Gain, Kitae Kim, Avi Deb Raha +4
In this paper, we propose the FedFeat+ framework, which distinctively separates feature extraction from classification. We develop a two-tiered model training process: following lo…
Boosting Federated Domain Generalization: Understanding the Role of Advanced Pre-Trained Architectures
Avi Deb Raha, Apurba Adhikary, Mrityunjoy Gain +2
In this study, we explore the efficacy of advanced pre-trained architectures, such as Vision Transformers (ViT), ConvNeXt, and Swin Transformers in enhancing Federated Domain Gener…
CCC: Color Classified Colorization
Mrityunjoy Gain, Avi Deb Raha, Rameswar Debnath
Automatic colorization of gray images with objects of different colors and sizes is challenging due to inter- and intra-object color variation and the small area of the main object…
CCC++: Optimized Color Classified Colorization with Segment Anything Model (SAM) Empowered Object Selective Color Harmonization
Mrityunjoy Gain, Avi Deb Raha, Rameswar Debnath
In this paper, we formulate the colorization problem into a multinomial classification problem and then apply a weighted function to classes. We propose a set of formulas to transf…