Logo Logo
Help
Contact
Switch language to German
Explainability and robustness of deep visual classification models
Explainability and robustness of deep visual classification models
Not available
Explainable AI, Adversarial Robustness, Vision Transformer, Capsule Network, Convolutional Neural Network
Gu, Jindong
2022
English
Universitätsbibliothek der Ludwig-Maximilians-Universität München
Gu, Jindong (2022): Explainability and robustness of deep visual classification models. Dissertation, LMU München: Faculty of Mathematics, Computer Science and Statistics
[thumbnail of Gu_Jindong.pdf]
Preview
 PDF
Gu_Jindong.pdf
36MB
DOI: 10.5282/edoc.30217
URN: urn:nbn:de:bvb:19-302171

Item Type:Theses (Dissertation, LMU Munich)
Keywords:Explainable AI, Adversarial Robustness, Vision Transformer, Capsule Network, Convolutional Neural Network
Subjects:000 Computers, Information and General Reference
000 Computers, Information and General Reference > 004 Data processing computer science
Faculties:Faculty of Mathematics, Computer Science and Statistics
Language:English
Date of oral examination:6. July 2022
1. Referee:Tresp, Volker
MD5 Checksum of the PDF-file:867ee5815d3aea1ff0ec9d7cdddbddd2
Signature of the printed copy:0001/UMC 28913
ID Code:30217
Deposited On:15. Jul 2022 12:18
Last Modified:15. Jul 2022 14:39
Repository Staff Only: item control page
Search for authors
Export

"Electronic Theses of LMU Munich" is powered by EPrints 3, which is developed by the School of Electronics and Computer Science at the University of Southampton.
Imprint - Privacy Disclaimer