Domain adaptation based on domain-invariant and class-distinguishable feature learning using multiple adversarial networks
Sign Up to like & getrecommendations! Published in 2020 at "Neurocomputing"
DOI: 10.1016/j.neucom.2020.06.044
Abstract: Abstract Adversarial networks have been used to learn transferable representations in many domain adaptation methods. However, there is no theoretical guarantee that two distributions are identical, even if the discriminator is fully confused. Therefore, a… read more here.
Keywords: adversarial networks; class; domain adversarial; central samples ... See more keywords
Domain adversarial transfer for cross-domain and task-constrained grasp pose detection
Sign Up to like & getrecommendations! Published in 2021 at "Robotics and Autonomous Systems"
DOI: 10.1016/j.robot.2021.103872
Abstract: Abstract Transferring the grasping skills learned from simulated environments to the real world is favorable for many robotic applications, in which the collecting and labeling processes of real-world visual grasping datasets are often expensive or… read more here.
Keywords: real world; task; task constrained; constrained grasp ... See more keywords
Domain-adversarial graph neural networks for Λ hyperon identification with CLAS12
Sign Up to like & getrecommendations! Published in 2023 at "Journal of Instrumentation"
DOI: 10.1088/1748-0221/18/06/p06002
Abstract: Machine learning methods and in particular Graph Neural Networks (GNNs) have revolutionized many tasks within the high energy physics community. Particularly in the realm of jet tagging, GNNs and domain adaptation have been especially successful.… read more here.
Keywords: neural networks; hyperon identification; domain adversarial; graph neural ... See more keywords
Domain Adversarial Neural Network-Based Intrusion Detection System for In-Vehicle Network Variant Attacks
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Communications Letters"
DOI: 10.1109/lcomm.2022.3195486
Abstract: A controller area network (CAN) bus that controls real-time communication and data transmission of electronic control units in vehicles lacks security mechanisms and is highly vulnerable to attacks. The detection effectiveness of existing In-Vehicle network… read more here.
Keywords: intrusion detection; network; domain adversarial; detection ... See more keywords
Domain-Adversarial Neural Networks for Deforestation Detection in Tropical Forests
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2022.3163575
Abstract: Many deep-learning (DL)-based, domain adaptation (DA) methods for remote sensing (RS) applications rely on adversarial training strategies to align features extracted from images of different domains in a shared latent space. However, the performance of… read more here.
Keywords: class; domain adversarial; detection; deforestation ... See more keywords
A New Structured Domain Adversarial Neural Network for Transfer Fault Diagnosis of Rolling Bearings Under Different Working Conditions
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Instrumentation and Measurement"
DOI: 10.1109/tim.2020.3038596
Abstract: This article presents a new deep transfer learning method, named structured domain adversarial neural network (SDANN), for bearing fault diagnosis with the data collected under different working conditions. The key idea of this method is… read more here.
Keywords: diagnosis; neural network; adversarial neural; transfer ... See more keywords