Federated domain generalization: A survey
Machine learning typically relies on the assumption that training and testing distributions are
identical and that data is centrally stored for training and testing. However, in real-world …
identical and that data is centrally stored for training and testing. However, in real-world …
Privacy-preserved generative network for trustworthy anomaly detection in smart grids: A federated semisupervised approach
M Abdel-Basset, N Moustafa… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
The deep integration of industrial internet of things technologies in the industrial smart grid
(ISG) brings many privacy and security attacks, threatening the trustworthiness of underlying …
(ISG) brings many privacy and security attacks, threatening the trustworthiness of underlying …
Federated ensemble-learning for transport mode detection in vehicular edge network
Abstract Transport Mode Detection (TMD) has become a crucial part of Intelligent
Transportation Systems (ITS) thanks to the recent advancements in Artificial Intelligence and …
Transportation Systems (ITS) thanks to the recent advancements in Artificial Intelligence and …
Survey of federated learning models for spatial-temporal mobility applications
Federated learning involves training statistical models over edge devices such as mobile
phones such that the training data is kept local. Federated Learning (FL) can serve as an …
phones such that the training data is kept local. Federated Learning (FL) can serve as an …
A multi-scale attributes fusion model for travel mode identification using GPS trajectories
K Fan, D Li, X Jin, S Wu - Geo-spatial Information Science, 2024 - Taylor & Francis
Travel mode recognition is a key issue in urban planning and transportation research. While
traditional travel surveys use manual data collection and have limited coverage, poor …
traditional travel surveys use manual data collection and have limited coverage, poor …
A multi-stage fusion network for transportation mode identification with varied scale representation of GPS trajectories
Accurate transportation mode identification is essential for traffic management and travel
planning. The rapid development of GPS-enabled devices has made it both popular and …
planning. The rapid development of GPS-enabled devices has made it both popular and …
Toward Industrial Densely Packed Object Detection: A Federated Semi-Supervised Learning Approach
Object detection through deep learning techniques plays a pivotal role in various industrial
applications, such as defect detection. With industries increasingly recognizing the …
applications, such as defect detection. With industries increasingly recognizing the …
A multi-modal tensor ring decomposition for communication-efficient and trustworthy federated learning for its in COVID-19 scenario
Traffic and the movement of people are inextricably associated with the potential spread of
COVID-19. In Intelligent Transportation System (ITS), Deep Learning (DL) traffic detection …
COVID-19. In Intelligent Transportation System (ITS), Deep Learning (DL) traffic detection …
Defense strategies toward model poisoning attacks in federated learning: A survey
Advances in distributed machine learning can empower future communications and
networking. The emergence of federated learning (FL) has provided an efficient framework …
networking. The emergence of federated learning (FL) has provided an efficient framework …
Enriching large-scale trips with fine-grained travel purposes: A semi-supervised deep graph embedding framework
Knowing why people travel is meaningful for human mobility understanding and smart
services development. Unfortunately, in real-world scenarios, trip purpose cannot be …
services development. Unfortunately, in real-world scenarios, trip purpose cannot be …