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Digital Watermarking for Machine Learning Model [[electronic resource] ] : Techniques, Protocols and Applications / / edited by Lixin Fan, Chee Seng Chan, Qiang Yang
Digital Watermarking for Machine Learning Model [[electronic resource] ] : Techniques, Protocols and Applications / / edited by Lixin Fan, Chee Seng Chan, Qiang Yang
Autore Fan Lixin
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (233 pages)
Disciplina 005.82
Altri autori (Persone) ChanChee Seng
YangQiang
Soggetto topico Machine learning
Data protection
Image processing—Digital techniques
Computer vision
Image processing
Machine Learning
Data and Information Security
Computer Imaging, Vision, Pattern Recognition and Graphics
Image Processing
Soggetto non controllato Engineering
Technology & Engineering
ISBN 981-19-7554-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Part I. Preliminary -- Chapter 1. Introduction -- Chapter 2. Ownership Verification Protocols for Deep Neural Network Watermarks -- Part II Techniques -- Chapter 3. ModelWatermarking for Image Recovery DNNs -- Chapter 4. The Robust and Harmless ModelWatermarking -- Chapter 5. Protecting Intellectual Property of Machine Learning Models via Fingerprinting the Classification Boundary -- Chapter 6. Protecting Image Processing Networks via Model Water -- Chapter 7. Watermarks for Deep Reinforcement Learning -- Chapter 8. Ownership Protection for Image Captioning Models -- Chapter 9.Protecting Recurrent Neural Network by Embedding Key -- Part III Applications -- Chapter 10. FedIPR: Ownership Verification for Federated Deep Neural Network Models -- Chapter 11. Model Auditing For Data Intellectual Property .
Record Nr. UNISA-996546839603316
Fan Lixin  
Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Digital Watermarking for Machine Learning Model : Techniques, Protocols and Applications / / edited by Lixin Fan, Chee Seng Chan, Qiang Yang
Digital Watermarking for Machine Learning Model : Techniques, Protocols and Applications / / edited by Lixin Fan, Chee Seng Chan, Qiang Yang
Autore Fan Lixin
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (233 pages)
Disciplina 005.82
Altri autori (Persone) ChanChee Seng
YangQiang
Soggetto topico Machine learning
Data protection
Image processing - Digital techniques
Computer vision
Image processing
Machine Learning
Data and Information Security
Computer Imaging, Vision, Pattern Recognition and Graphics
Image Processing
ISBN 9789811975547
981197554X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Part I. Preliminary -- Chapter 1. Introduction -- Chapter 2. Ownership Verification Protocols for Deep Neural Network Watermarks -- Part II Techniques -- Chapter 3. ModelWatermarking for Image Recovery DNNs -- Chapter 4. The Robust and Harmless ModelWatermarking -- Chapter 5. Protecting Intellectual Property of Machine Learning Models via Fingerprinting the Classification Boundary -- Chapter 6. Protecting Image Processing Networks via Model Water -- Chapter 7. Watermarks for Deep Reinforcement Learning -- Chapter 8. Ownership Protection for Image Captioning Models -- Chapter 9.Protecting Recurrent Neural Network by Embedding Key -- Part III Applications -- Chapter 10. FedIPR: Ownership Verification for Federated Deep Neural Network Models -- Chapter 11. Model Auditing For Data Intellectual Property .
Record Nr. UNINA-9910728383303321
Fan Lixin  
Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui