
Federated learning for Internet of Vehicles: IoV Image Processing, Vision and Intelligent Systems
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Federated learning for Internet of Vehicles: IoV Image Processing, Vision and Intelligent Systems
About this book
This handbook provides a comprehensive understanding of computational linguistics, focusing on the integration of deep learning in natural language processing (NLP). 18 edited chapters cover the state-of-the-art theoretical and experimental research on NLP, offering insights into advanced models and recent applications. Highlights: - Foundations of NLP: Provides an in-depth study of natural language processing, including basics, challenges, and applications. - Advanced NLP Techniques: Explores recent advancements in text summarization, machine translation, and deep learning applications in NLP. - Practical Applications: Demonstrates use cases on text identification from hazy images, speech-to-sign language translation, and word sense disambiguation using deep learning. - Future Directions: Includes discussions on the future of NLP, including transfer learning, beyond syntax and semantics, and emerging challenges. Key Features: - Comprehensive coverage of NLP and deep learning integration. - Practical insights into real-world applications - Detailed exploration of recent research and advancements through 16 easy to read chapters - References and notes on experimental methods used for advanced readers Ideal for researchers, students, and professionals, this book offers a thorough understanding of computational linguistics by equipping readers with the knowledge to understand how computational techniques are applied to understand text, language and speech. Readership Researchers, students, and professionals in computer science and related fields (AI, ML, NLP and computational linguistics).
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Table of contents
- Welcome
- Table of Content
- Title
- BENTHAM SCIENCE PUBLISHERS LTD.
- PREFACE
- List of Contributors
- A Comprehensive Study of Natural Language Processing
- Recent Advancements in Text Summarization with Natural Language Processing
- Learning Techniques for Natural Language Processing: An Overview
- Natural Language Processing: Basics, Challenges, and Clustering Applications
- Hybrid Approach to Text Translation in NLP Using Deep Learning and Ensemble Method
- Deep Learning in Natural Language Processing
- Deep Learning-Based Text Identification from Hazy Images: A Self-Collected Dataset Approach
- Deep Learning-based Word Sense Disambiguation for Hindi Language Using Hindi WordNet Dataset
- The Machine Translation Systems Demystifying the Approaches
- Machine Translation of English to Hindi with the LSTM Seq2Seq Model Utilizing Attention Mechanism
- Natural Language Processing: A Historical Overview, Current Developments, and Future Prospects
- Recent Advances in Transfer Learning for Natural Language Processing (NLP)
- Beyond Syntax and Semantics: The Quantum Leap in Natural Language Processing
- Text Extraction from Blurred Images through NLP-based Post-processing
- Speech-to-Sign Language Translator Using NLP
- Speech Technologies
- The Linguistic Frontier: Unleashing the Power of Natural Language Processing in Cybersecurity
- Recent Challenges and Advancements in Natural Language Processing