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Undergraduate Titles > Computer Science
Multimodal Machine Learning: Techniques and Applications
Kumar, Santosh
ISBN 13: 
9780128237373
ISBN 10: 
0128237376
Category: 
Computer Science
Edition: 
1
Publisher: 
Elsevier
Publication Date: 
12/2025
Format: 
Paperback
Status: 
Not Yet Published
Imprint: 
Academic Press
Audience: 
Professional and scholarly
Pages: 
375
Weight: 
2
Retail Price: 
125.00 (Tentative Price May Change)
Quantity On Hand: 
0
Quantity On Order: 
0
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Synopsis:
Multimodal Machine Learning: Techniques and Applications explains recent advances in multimodal machine learning, providing a coherent set of fundamentals for designing efficient multimodal learning algorithms for different applications. The book addresses the main challenges in multimodal machine learning based computing paradigms, including multimodal representation learning, translation and mapping, modality alignment, multimodal fusion and co-learning. The book also explores the important texture feature descriptors based on recognition and transform techniques. It is ideal for senior undergraduates, graduate students, and researchers in data science, engineering, computer science and statistics.

  • Presents new representation, classification and identification algorithms for data prediction and analysis on feature characteristics
  • Discusses recent and future advancements in diversified fields of computer vision , pattern recognition, generative adversarial network-based learning, video analytics and data science
  • Provides an overview of future research challenges and directions

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