Federated learning for medical image analysis: A survey
Abstract Machine learning in medical imaging often faces a fundamental dilemma, namely,
the small sample size problem. Many recent studies suggest using multi-domain data …
the small sample size problem. Many recent studies suggest using multi-domain data …
Memory-aware curriculum federated learning for breast cancer classification
Abstract Background and Objective: For early breast cancer detection, regular screening
with mammography imaging is recommended. Routine examinations result in datasets with …
with mammography imaging is recommended. Routine examinations result in datasets with …
Federated learning for healthcare applications
Due to the fast advancement of artificial intelligence (AI), centralized-based models have
become critical for healthcare tasks like in medical image analysis and human behavior …
become critical for healthcare tasks like in medical image analysis and human behavior …
Federated learning with non-iid data: A survey
Z Lu, H Pan, Y Dai, X Si, Y Zhang - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
Federated learning (FL) is an efficient decentralized machine learning methodology for
processing nonindependent and identically distributed (non-IID) data due to geographical …
processing nonindependent and identically distributed (non-IID) data due to geographical …
Federated learning for computer vision
Computer Vision (CV) is playing a significant role in transforming society by utilizing
machine learning (ML) tools for a wide range of tasks. However, the need for large-scale …
machine learning (ML) tools for a wide range of tasks. However, the need for large-scale …
HFedDI: A novel privacy preserving horizontal federated learning based scheme for IoT device identification
MV Shenoy - Journal of Network and Computer Applications, 2023 - Elsevier
As the number of IoT devices that are getting connected to the Internet is increasing, there is
a need to automatically detect the IoT devices connected to the network for efficient network …
a need to automatically detect the IoT devices connected to the network for efficient network …
Federated medical image analysis with virtual sample synthesis
Hospitals and research institutions may not be willing to share their collected medical data
due to privacy concerns, transmission cost, and the intrinsic value of the data. Federated …
due to privacy concerns, transmission cost, and the intrinsic value of the data. Federated …
A new federated learning-based wireless communication and client scheduling solution for combating COVID-19
Federated learning is a machine learning method that can break the data island. Its inherent
privacy-preserving property has an important role in training medical image models …
privacy-preserving property has an important role in training medical image models …
[HTML][HTML] Polarimetric Synthetic Aperture Radar Image Classification Based on Double-Channel Convolution Network and Edge-Preserving Markov Random Field
J Shi, M Nie, S Ji, C Shi, H Liu, H Jin - Remote Sensing, 2023 - mdpi.com
Deep learning methods have gained significant popularity in the field of polarimetric
synthetic aperture radar (PolSAR) image classification. These methods aim to extract high …
synthetic aperture radar (PolSAR) image classification. These methods aim to extract high …
Cross-Silo, Privacy-Preserving, and Lightweight Federated Multimodal System for the Identification of Major Depressive Disorder Using Audio and …
In this day and age, depression is still one of the biggest problems in the world. If left
untreated, it can lead to suicidal thoughts and attempts. There is a need for proper …
untreated, it can lead to suicidal thoughts and attempts. There is a need for proper …