Fast and Scalable Earth Texture Synthesis using Spatially Assembled Generative Adversarial Neural Networks
Sign Up to like & getrecommendations! Published in 2021 at "Journal of contaminant hydrology"
DOI: 10.1016/j.jconhyd.2021.103867
Abstract: The earth texture with complex morphological geometry and compositions such as shale and carbonate rocks, is typically characterized with sparse field samples because of an expensive and time-consuming characterization process. Accordingly, generating arbitrary large size… read more here.
Keywords: generative adversarial; neural networks; earth texture; size ... 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
Heterogeneous Domain Adaptation With Adversarial Neural Representation Learning: Experiments on E-Commerce and Cybersecurity
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Pattern Analysis and Machine Intelligence"
DOI: 10.1109/tpami.2022.3163338
Abstract: Learning predictive models in new domains with scarce training data is a growing challenge in modern supervised learning scenarios. This incentivizes developing domain adaptation methods that leverage the knowledge in known domains (source) and adapt… read more here.
Keywords: domain adaptation; heterogeneous domain; adaptation adversarial; domain ... See more keywords