Artificial intelligence and computer vision
- Responsibility
- Huimin Lu, Yujie Li, editors.
- Publication
- Cham : Springer, [2016]
- Copyright notice
- ©2017
- Physical description
- 1 online resource (x, 211 pages) : illustrations (some color)
- Series
- Studies in computational intelligence ; v. 672. 1860-949X
Online
Available online
More options
Description
Creators/Contributors
- Contributor
- Lu, Huimin, editor.
- Li, Yujie editor.
Contents/Summary
- Contents
-
- Computer Vision for Ocean Observing
- Fault Diagnosis and Classification of Mine Motor based on RS and SVM
- Particle Swarm Optimization based Image Enhancement of Visual Cryptography Shares
- Fast Level set Algorithm for Extraction and Evaluation of Weld Defects in Radiographic Images
- Efficient Combination of Color, Texture and Shape Descriptor, using SLIC Segmentation for Image Retrieval
- DEPO: Detecting Events of Public Opinion in Microblog
- Hybrid Cuckoo Search based Evolutionary Vector Quantization for Image Compression
- Edge and Fuzzy Transform based Image Compression Algorithm: edgeFuzzy
- Real-Time Implementation of Moving Object Action Recognition System Based on Motion Analysis
- Cross-modal Learning with Images, Texts and Their Semantics
- Light Field Vision for Artificial Intelligence
- Author Index.
- Summary
- This edited book presents essential findings in the research fields of artificial intelligence and computer vision, with a primary focus on new research ideas and results for mathematical problems involved in computer vision systems. The book provides an international forum for researchers to summarize the most recent developments and ideas in the field, with a special emphasis on the technical and observational results obtained in the past few years.
Subjects
Bibliographic information
- Publication date
- 2016
- Copyright date
- 2017
- Series
- Studies in computational intelligence, 1860-949X ; volume 672
- Note
- Includes author index.
- ISBN
- 9783319462455 (electronic bk.)
- 3319462458 (electronic bk.)
- 9783319462448 (print)
- DOI
- 10.1007/978-3-319-46245-5
