Feature dimension reduction for content-based image identification /
"This book explores various research applications in the complementary fields of 3D image processing. It covers segmentation techniques for feature reduction, clustering techniques for feature reduction, early fusion of extracted features, late fusion of classification decision, supervised lear...
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Corporate Authors: | |
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Group Author: | ; ; |
Published: |
IGI Global,
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Publisher Address: | Hershey, Pa. : |
Publication Dates: | [2019] |
Literature type: | eBook |
Language: | English |
Subjects: | |
Online Access: |
http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-5775-3 |
Summary: |
"This book explores various research applications in the complementary fields of 3D image processing. It covers segmentation techniques for feature reduction, clustering techniques for feature reduction, early fusion of extracted features, late fusion of classification decision, supervised learning and unsupervised learning techniques"-- |
Carrier Form: | 21 PDFs (xix, 284 pages) |
Bibliography: | Includes bibliographical references and index. |
ISBN: | 9781522557760 |
Access: | Restricted to subscribers or individual electronic text purchasers. |
Index Number: | TA1650 |
CLC: | TP391.4-532 |
Contents: | Chapter 1. An integrated framework for information identification with image data using multi-technique feature extraction -- Chapter 2. Dimension reduction using image transform for content-based feature extraction -- Chapter 3. Fuzzy techniques for content-based image retrieval -- Chapter 4. Machine-learning-based image feature selection -- Chapter 5. Feature selection using neighborhood positive approximation rough set -- Chapter 6. Clustering techniques for content-based feature extraction from image -- Chapter 7. Machine-learning-based external plagiarism detecting methodology from monolingual documents: a comparative study -- Chapter 8. Segmentation of multiple touching hand written devnagari compound characters: image segmentation for feature extraction -- Chapter 9. Logo matching and recognition based on context -- Chapter 10. Detecting and tracking segmentation of moving objects using graph cut algorithm -- Chapter 11. Deep-learning-based classification and diagnosis of Alzheimer's disease -- Chapter 12. Application of object recognition with shape-index identification and 2d scale invariant feature transform for key-point detection -- Chapter 13. Image segmentation for feature extraction: a study on disease diagnosis in agricultural plants. |