Case Studies in Intelligent Computing
Achievements and Trends
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Case Studies in Intelligent Computing
Description
Although the field of intelligent systems has grown rapidly in recent years, there has been a need for a book that supplies a timely and accessible understanding of this important technology. Filling this need, Case Studies in Intelligent Computing: Achievements and Trends provides an up-to-date introduction to intelligent systems.
This edited book captures the state of the art in intelligent computing research through case studies that examine recent developments, developmental tools, programming, and approaches related to artificial intelligence (AI). The case studies illustrate successful machine learning and AI-based applications across various industries, including:
- A non-invasive and instant disease detection technique based upon machine vision through the image scanning of the eyes of subjects with conjunctivitis and jaundice
- Semantic orientation-based approaches for sentiment analysis
- An efficient and autonomous method for distinguishing application protocols through the use of a dynamic protocol classification system
- Nonwavelet and wavelet image denoising methods using fuzzy logic
- Using remote sensing inputs based on swarm intelligence for strategic decision making in modern warfare
- Rainfall-runoff modeling using a wavelet-based artificial neural network (WANN) model
Illustrating the challenges currently facing practitioners, the book presents powerful solutions recently proposed by leading researchers. The examination of the various case studies will help you develop the practical understanding required to participate in the advancement of intelligent computing applications.
The book will help budding researchers understand how and where intelligent computing can be applied. It will also help more established researchers update their skills and fine-tune their approach to intelligent computing.
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