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 | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
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 | ||
| Lo trovi qui: Univ. Federico II | ||
| ||