Understanding-Oriented Multimedia Content Analysis
by Zechao Li
Publisher: Springer
৳ 350.00
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Understanding-Oriented Multimedia Content Analysis
Overview:
This book offers a systematic introduction to an understanding-oriented approach to multimedia content analysis. It focuses on integrating visual understanding and learning models into a unified framework. In this framework, visual understanding guides the model learning, while the learned models in turn improve the visual understanding.
Key Topics Covered:
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Multimedia Content Representation & Analysis
- Feature selection and feature extraction techniques.
- Image tagging and user-oriented tag recommendation.
- Understanding-oriented multimedia applications.
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Unified Framework
- How the integration of visual understanding and model learning enhances multimedia analysis.
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Technologies & Methods
- Introduction to the fundamental technologies and cutting-edge methods in multimedia content analysis.
Recognition:
This book was nominated by the University of Chinese Academy of Sciences and the China Computer Federation as an outstanding PhD thesis.
Ideal for:
Graduate students and researchers in computer vision, machine learning, and multimedia content analysis. The book offers in-depth theoretical insights and practical methodologies that will be valuable for advancing research in the field.
A must-read for anyone interested in the intersection of visual understanding and machine learning in multimedia a
Name: Zechao Li, Ph.D.
Current Position: Full Professor at Nanjing University of Science and Technology, China, and Vice Dean of the Schools of Computer Science, Artificial Intelligence, and Software Engineering.
Academic Background
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Bachelor’s degree from the University of Science and Technology of China (USTC), 2008
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Ph.D. from the National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, 2013
Research Areas & Expertise
Zechao Li is a leading researcher in:
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Multimedia analysis
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Computer vision
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Machine learning
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Object detection and semantic segmentation
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Few-shot learning and deep learning for image/video understanding
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Cross-media intelligent analysis, image hashing, efficient retrieval, and social multimedia analytics
Achievements & Recognition
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Author of 90+ research papers published in top-tier international journals and conferences
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Recipient of major scientific awards, including:
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Best Paper Award at ACM Multimedia Asia (2020)
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First Prize of the Natural Science Award of the Chinese Institute of Electronics (2022)
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First Prize of the Science and Technology Award of Jiangsu Province (2017, 2020)
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Listed as one of Elsevier’s Highly Cited Chinese Researchers for multiple consecutive years
Why His Work Matters
Zechao Li’s research advances modern artificial intelligence with impactful contributions in image understanding, semantic segmentation, and large-scale multimedia retrieval. His work is widely cited and influences both academic research and real-world AI applications. Students, scholars, and industry professionals benefit greatly from his innovative approaches to intelligent multimedia systems.
Springer is one of the world’s oldest and most respected academic and scientific publishers. The company traces its origin to 1842, when Julius Springer founded a bookshop and publishing house in Berlin, which later grew into one of the largest global publishers of scientific, technical, and medical literature.
Key Facts
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Founded: 1842 (as Springer-Verlag in Berlin).
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Why Springer Is Trusted / What Makes It Stand Out
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Legacy & Reputation: With a legacy of nearly 180 years in academic publishing, Springer has established a reputation for quality scholarly works.
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Wide Disciplinary Coverage: Whether it’s hard sciences, medicine, engineering, social sciences or humanities — Springer caters to a very broad academic audience. This makes it versatile and widely used among universities and research institutions globally.
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