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Structural, Syntactic, and Statistical Pattern Recognition : Joint IAPR International Workshops, S+SSPR 2020, Padua, Italy, January 21-22, 2021, Proceedings / edited by Andrea Torsello, Luca Rossi, Marcello Pelillo, Battista Biggio, Antonio Robles-Kelly.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- LNCS sublibrary. Image processing, computer vision, pattern recognition, and graphics ; SL 6, 12644
- Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 12644
- Language:
- English
- Subjects (All):
- Artificial intelligence.
- Algorithms.
- Artificial intelligence-Data processing.
- Social sciences-Data processing.
- Computers.
- Computer science-Mathematics.
- Artificial Intelligence.
- Data Science.
- Computer Application in Social and Behavioral Sciences.
- Computing Milieux.
- Mathematics of Computing.
- Local Subjects:
- Artificial Intelligence.
- Algorithms.
- Data Science.
- Computer Application in Social and Behavioral Sciences.
- Computing Milieux.
- Mathematics of Computing.
- Physical Description:
- 1 online resource (XII, 378 pages) : 103 illustrations, 84 illustrations in color.
- Edition:
- 1st ed. 2021.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2021.
- System Details:
- text file PDF
- Summary:
- This book constitutes the proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition, S+SSPR 2020, held in Padua, Italy, in January 2021. The 35 papers presented in this volume were carefully reviewed and selected from 81 submissions. The accepted papers cover the major topics of current interest in pattern recognition, including classification and clustering, deep learning, structural matching and graph-theoretic methods, and multimedia analysis and understanding.
- Contents:
- Classification and data processing
- Deep learning
- Graph-theoretic methods
- Multimedia analysis and understanding.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-030-73973-7
- 9783030739737
- Access Restriction:
- Restricted for use by site license.
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