Atnaujinkite slapukų nuostatas

El. knyga: Iris and Periocular Recognition using Deep Learning

(Department of Computing, The Hong Kong Polytechnic University Hong Kong, Kowloon, Hong Kong)
  • Formatas: EPUB+DRM
  • Išleidimo metai: 12-Jun-2024
  • Leidėjas: Academic Press Inc
  • Kalba: eng
  • ISBN-13: 9780443273193
  • Formatas: EPUB+DRM
  • Išleidimo metai: 12-Jun-2024
  • Leidėjas: Academic Press Inc
  • Kalba: eng
  • ISBN-13: 9780443273193

DRM apribojimai

  • Kopijuoti:

    neleidžiama

  • Spausdinti:

    neleidžiama

  • El. knygos naudojimas:

    Skaitmeninių teisių valdymas (DRM)
    Leidykla pateikė šią knygą šifruota forma, o tai reiškia, kad norint ją atrakinti ir perskaityti reikia įdiegti nemokamą programinę įrangą. Norint skaityti šią el. knygą, turite susikurti Adobe ID . Daugiau informacijos  čia. El. knygą galima atsisiųsti į 6 įrenginius (vienas vartotojas su tuo pačiu Adobe ID).

    Reikalinga programinė įranga
    Norint skaityti šią el. knygą mobiliajame įrenginyje (telefone ar planšetiniame kompiuteryje), turite įdiegti šią nemokamą programėlę: PocketBook Reader (iOS / Android)

    Norint skaityti šią el. knygą asmeniniame arba „Mac“ kompiuteryje, Jums reikalinga  Adobe Digital Editions “ (tai nemokama programa, specialiai sukurta el. knygoms. Tai nėra tas pats, kas „Adobe Reader“, kurią tikriausiai jau turite savo kompiuteryje.)

    Negalite skaityti šios el. knygos naudodami „Amazon Kindle“.

Iris and Periocular Recognition using Deep Learning systematically explains the fundamental and most advanced techniques for ocular imprint-based human identification, with many applications in sectors such as healthcare, online education, e-business, metaverse, and entertainment. This is the first-ever book devoted to iris recognition that details cutting-edge techniques using deep neural networks. This book systematically introduces such algorithmic details with attractive illustrations, examples, experimental comparisons, and security analysis. It answers many fundamental questions about the most effective iris and periocular recognition techniques.

1. Advances in Iris and Ocular Recognition: An Insight into Trends
2. Unlocking the Full Potential of Iris Recognition with Deep Learning
3. Real-Time Online Framework for Accurate Detection, Segmentation, and Recognition of Irises
4. Enhancing Iris Recognition Accuracy through Dilated Residual Features
5. Iris Recognition with Deep Learning Across Spectrums
6. Semantics-Assisted Convolutional Neural Network for Accurate Periocular Recognition
7. Deep Neural Network with Focused Attention on Critical Periocular Regions
8. Dynamic Iris Recognition through Multi-Feature Collaboration
9. Position-Specific Convolutional Neural Network to Accurately Match Iris and Periocular Images
10. Securing the Metaverse with Egocentric Iris Recognition via AR/VR/MR Devices
11. Inference and Future Pathways: Reflections and Exploration of New Horizons

Ajay Kumar is a Professor in the Department of Computing at The Hong Kong Polytechnic University, Hong Kong. Prior to this, he served as an Assistant Professor in the Department of Electrical Engineering at IIT Delhi from 2005 to 2007. Dr. Kumar serves on the Editorial Board of IEEE Transactions on Pattern Analysis and Machine Intelligence. He is a Fellow of IEEE and IAPR and has served the IEEE Biometrics Council as its President from 2021 to 2022. His research interests include biometrics with an emphasis on iris, hand, and knuckle biometrics.