Browsing by Subject "Federated learning"
Now showing items 1-14 of 14
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An advanced data fabric architecture leveraging homomorphic encryption and federated learning
(Brac University, 2023-03)In this study, we present a novel approach for securely analyzing medical images using federated learning and partially homomorphic encryption within a distributed data fabric architecture. Our approach allows multiple ... -
Analyzing the security of e-Health data based on a hybrid federated learning model
(Brac University, 2023-01)This research aims to provide an approach for analyzing the security of the e-health care system through the use of federated learning and the pre-processing of distinct deep learning models. The infrastructure for ... -
An autoencoder-based decentralized clustering leveraging model aggregation fusion strategy
(Brac University, 2024-05)Unsupervised clustering plays a crucial role in various real-life applications. It works by grouping similar data points together based on certain features or characteristics, without the use of predefined labels. The ... -
EAI4CC: deciphering lung and colon cancer categorization within a federated learning framework harnessing the power of explainable artificial intelligence
(Brac University, 2024-01)Advances between medical imaging and artificial intelligence (AI) have led to improvements in cancer diagnosis and classification. This paper provides a new framework called Explainable AI for cancer categorization ... -
Federated ensemble-learning for transport mode detection in vehicular edge network
(Brac University, 2023-01)Transport Mode detection has become a crucial part of Intelligent Transportation Systems (ITS) and Traffic Management Systems due to the recent advancements in Artificial Intelligent (AI) and the Internet of Things (IoT). ... -
A federated learning approach for detecting Parkinson’s disease through privacy preserving by blockchain
(Brac University, 2022-05)Parkinson’s disease is a degenerative ailment caused by the loss of nerve cells in the brain region known as the Substantia Nigra, which governs movement. These nerve cells die or deteriorate, rendering them unable to ... -
Fortifying federated learning: security against model poisoning attacks
(Brac University, 2024-01)Distributed machine learning advancements have the potential to transform future networking systems and communications. An effective framework for machine learning has been made possible by the introduction of Federated ... -
A hybrid FL-Enabled ensemble approach for lung disease diagnosis leveraging fusion of SWIN transformer and CNN
(Brac University, 2022-09-22)The significant advancements in computational power create the vast opportunity for using Artificial Intelligence in different applications of healthcare and medical science. A Hybrid FL-Enabled Ensemble Approach For Lung ... -
Personalization in federated recommendation system using SVD++ with explainability
(Brac University, 2022-01)Large-scale distributed Artificial Intelligence (AI) systems are getting more widespread as traditional AI applications require centralizing large amounts of data for training models, posing privacy and security risks. ... -
Prediction of genetic mutation from clinical data of sickle cell disease using few-shot siamese bidirectional LSTM and federated learning
(Brac University, 2023-05)Sickle Cell Disease is a monogenic genetic disorder which often leads to various repercussions affecting multiple vital organs simultaneously. However, the treat- ment for Sickle Cell is diverse and often varies from ... -
Privacy focused classification of prostate cancer using federated learning
(Brac University, 2022-01)The prostate gland is a small gland located in the lower abdomen of a man. Prostate cancer occurs when a tumor, or abnormal, malignant growth of cells, forms in the prostate. Prostate cancer is a slow-growing cancer that ... -
ResInvolution: an involution-ResNet fused global spatial relation leveraging model for histopathological image analysis under federated learning environment
(Brac University, 2024-05)Accessing image data in the domain of medical image analysis is challenging owing to concerns regarding privacy. Federated Learning is the approach used to get rid of this challenge. With millions of learning parameters, ... -
A secured federated learning system leveraging confidence score to identify retinal disease
(Brac University, 2023-05)Federated learning is a distributed machine learning paradigm that enables multiple clients to collaboratively train a global model without sharing their local data. How- ever, federated learning is vulnerable to adversarial ... -
A semi-supervised federated learning approach leveraging pseudo-labeling for Knee Osteoarthritis severity detection
(Brac University, 2024-06)Within medical image analysis, appropriately classifying the extent of knee osteoarthritis is a significant obstacle, made more difficult by the scarcity of annotated data and strict privacy rules. Conventional approaches ...
