Generative Adversarial Networks for Heterogeneous Unsupervised Domain Adaptation Detection-Reference-Cited by-同舟云学术

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Generative Adversarial Networks for Heterogeneous Unsupervised Domain Adaptation Detection

Published:2024-07-17 Issue: Volume:34 Page:000235-000244
ISSN:
Container-title:2024 IEEE 28th International Conference on Intelligent Engineering Systems (INES)
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Author:

Mahalegi Homayoun Safarpour Motealegh¹,Farhadi Amirfarhad²,Molnár György³,Nagy Enikő⁴

Affiliation:

1. Óbuda University,Institute of Mechatronics and Vehicle Engineering,Budapest,Hungary

2. Islamic Azad University,Science and Research Branch,Department of Computer Engineering,Tehran,Iran

3. Óbuda University,Kandó Kálmán Faculty of Electrical Engineering,Budapest,Hungary

4. Óbuda University,Antal Bejczy Center for Intelligent Robotics, John von Neumann Faculty of Informatics,Budapest,Hungary

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10629055/10629080/10629101.pdf?arnumber=10629101

Reference34 articles.

1. Intelligent solid waste classification using deep convolutional neural networks

2. Multi-Scale Fully Convolutional Network-Based Semantic Segmentation for Mobile Robot Navigation

3. SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

4. Hippocampus Segmentation Using U-Net Convolutional Network from Brain Magnetic Resonance Imaging (MRI)

5. AM-PSPNet: Pyramid Scene Parsing Network Based on Attentional Mechanism for Image Semantic Segmentation

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