Image Analysis and Recognition [[electronic resource] ] : 16th International Conference, ICIAR 2019, Waterloo, ON, Canada, August 27–29, 2019, Proceedings, Part I / / edited by Fakhri Karray, Aurélio Campilho, Alfred Yu

• Record Nr.: UNISA996466438603316
• Pubbl/distr/stampa: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019
• ISBN: 3-030-27202-8
• Edizione: [1st ed. 2019.]
• Descrizione fisica: 1 online resource (XXI, 475 p. 363 illus., 137 illus. in color.)
• Collana: Image Processing, Computer Vision, Pattern Recognition, and Graphics ; ; 11662
• Disciplina: 006.37
• Soggetti: Optical data processing; Artificial intelligence; Computers; Computer security; Data encryption (Computer science); Image Processing and Computer Vision; Artificial Intelligence; Information Systems and Communication Service; Systems and Data Security; Cryptology
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Sommario/riassunto: This two-volume set LNCS 11662 and 11663 constitutes the refereed proceedings of the 16th International Conference on Image Analysis and Recognition, ICIAR 2019, held in Waterloo, ON, Canada, in August 2019. The 58 full papers presented together with 24 short and 2 poster papers were carefully reviewed and selected from 142 submissions. The papers are organized in the following topical sections: Image Processing; Image Analysis; Signal Processing Techniques for Ultrasound Tissue Characterization and Imaging in Complex Biological ; Media; Advances in Deep Learning; Deep Learning on the Edge; Recognition; Applications; Medical Imaging and Analysis Using Deep Learning and Machine Intelligence; Image Analysis and Recognition for Automotive Industry; Adaptive Methods for Ultrasound Beamforming and Motion Estimation.

Privacy-preserving machine learning for speech processing / / Manas A. Pathak

• Record Nr.: UNINA9910437900603321
• Pubbl/distr/stampa: New York, : Springer, 2012
• ISBN: 1-283-91048-9; 1-4614-4639-2
• Edizione: [1st ed. 2013.]
• Descrizione fisica: 1 online resource (144 p.)
• Collana: Springer theses
• Altri autori (Persone): PathakManas A
• Disciplina: 004.2/1; 621.3994
• Soggetti: Speech processing systems; Machine learning
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: "Doctoral thesis accepted by Carnegie Mellon University, USA".
• Nota di contenuto: Thesis Overview -- Speech Processing Background -- Privacy Background -- Overview of Speaker Verification with Privacy -- Privacy-Preserving Speaker Verification Using Gaussian Mixture Models -- Privacy-Preserving Speaker Verification as String Comparison -- Overview of Speaker Identification with Privacy -- Privacy-Preserving Speaker Identification Using Gausian Mixture Models -- Privacy-Preserving Speaker Identification as String Comparison -- Overview of Speech Recognition with Privacy -- Privacy-Preserving Isolated-Word Recognition -- Thesis Conclusion -- Future Work -- Differentially Private Gaussian Mixture Models.
• Sommario/riassunto: This thesis discusses the privacy issues in speech-based applications, including biometric authentication, surveillance, and external speech processing services. Manas A. Pathak presents solutions for privacy-; preserving speech processing applications such as speaker verification, speaker identification, and speech recognition. The thesis introduces tools from cryptography and machine learning and current techniques for improving the efficiency and scalability of the presented solutions, as well as experiments with prototype implementations of the solutions for execution time and accuracy on standardized speech datasets. Using the framework proposed may make it possible for a surveillance agency to listen for a known terrorist, without being able to hear conversation from non-targeted, innocent civilians.