Transfer learning promotes 6G wireless communications: Recent advances and future challenges
M Wang, Y Lin, Q Tian, G Si - IEEE Transactions on Reliability, 2021 - ieeexplore.ieee.org
In the coming 6G communications, network densification, high throughput, positioning
accuracy, energy efficiency, and many other key performance indicator requirements are …
accuracy, energy efficiency, and many other key performance indicator requirements are …
Transfer adaptation learning: A decade survey
The world we see is ever-changing and it always changes with people, things, and the
environment. Domain is referred to as the state of the world at a certain moment. A research …
environment. Domain is referred to as the state of the world at a certain moment. A research …
A survey on deep transfer learning
As a new classification platform, deep learning has recently received increasing attention
from researchers and has been successfully applied to many domains. In some domains …
from researchers and has been successfully applied to many domains. In some domains …
Visual domain adaptation with manifold embedded distribution alignment
Visual domain adaptation aims to learn robust classifiers for the target domain by leveraging
knowledge from a source domain. Existing methods either attempt to align the cross-domain …
knowledge from a source domain. Existing methods either attempt to align the cross-domain …
Transfer learning with dynamic distribution adaptation
Transfer learning aims to learn robust classifiers for the target domain by leveraging
knowledge from a source domain. Since the source and the target domains are usually from …
knowledge from a source domain. Since the source and the target domains are usually from …
State-of-health estimation of lithium-ion batteries based on semi-supervised transfer component analysis
Accurate state-of-health estimation can ensure the safe and reliable operation of Lithium-ion
batteries in any given application. Nevertheless, most of the state-of-health estimation …
batteries in any given application. Nevertheless, most of the state-of-health estimation …
Transfer learning
SJ Pan - Learning, 2020 - api.taylorfrancis.com
Supervised machine learning techniques have already been widely studied and applied to
various real-world applications. However, most existing supervised algorithms work well …
various real-world applications. However, most existing supervised algorithms work well …
Deep learning-based fault diagnosis of photovoltaic systems: A comprehensive review and enhancement prospects
Photovoltaic (PV) systems are subject to failures during their operation due to the aging
effects and external/environmental conditions. These faults may affect the different system …
effects and external/environmental conditions. These faults may affect the different system …
Fedsteg: A federated transfer learning framework for secure image steganalysis
The protection of user private data has long been the focus of AI security. We know that
training machine learning models rely on large amounts of user data. However, user data …
training machine learning models rely on large amounts of user data. However, user data …
Software visualization and deep transfer learning for effective software defect prediction
Software defect prediction aims to automatically locate defective code modules to better
focus testing resources and human effort. Typically, software defect prediction pipelines are …
focus testing resources and human effort. Typically, software defect prediction pipelines are …