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3D Imaging Technologies--Multidimensional Signal Processing and Deep Learning: Methods, Algorithms and Applications, Volume 2

ISBN-13: 9789811631795 / Angielski / Twarda / 2021 / 309 str.

Lakhmi C. Jain; Roumen Kountchev; Yonghang Tai
3D Imaging Technologies--Multidimensional Signal Processing and Deep Learning: Methods, Algorithms and Applications, Volume 2 Jain, Lakhmi C. 9789811631795 Springer - książkaWidoczna okładka, to zdjęcie poglądowe, a rzeczywista szata graficzna może różnić się od prezentowanej.

3D Imaging Technologies--Multidimensional Signal Processing and Deep Learning: Methods, Algorithms and Applications, Volume 2

ISBN-13: 9789811631795 / Angielski / Twarda / 2021 / 309 str.

Lakhmi C. Jain; Roumen Kountchev; Yonghang Tai
cena 1008,75
(netto: 960,71 VAT:  5%)

Najniższa cena z 30 dni: 963,86
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inne wydania
Kategorie:
Technologie
Kategorie BISAC:
Technology & Engineering > Engineering (General)
Computers > Artificial Intelligence - General
Technology & Engineering > Electronics - General
Wydawca:
Springer
Seria wydawnicza:
Smart Innovation, Systems and Technologies
Język:
Angielski
ISBN-13:
9789811631795
Rok wydania:
2021
Wydanie:
2021
Numer serii:
000405987
Ilość stron:
309
Waga:
0.65 kg
Wymiary:
23.39 x 15.6 x 2.06
Oprawa:
Twarda
Wolumenów:
01
Dodatkowe informacje:
Wydanie ilustrowane

Chapter 1. Short-Term Traffic Volume Prediction Based on Gray Wolf Optimization Algorithm.- Chapter 2. Research on Car Seat Comfort Evaluation System Based on Chinese Population.- Chapter 3. Classification Method Active Pulmonary Tuberculosis With 3D Texture Features From CT Images.- Chapter 4. Research on Building Extraction from High Resolution Remote Sensing Image Based on Improved U-Net.- Chapter 5. A Survey of Image Classification Algorithms Based on Graph Neural Networks.- Chapter 6. Biological Particle Recognition Based on BP Neural Network Algorithm.- Chapter 7. License Plate Recognition System Based on OpenCV.- Chapter 8. ImageCube: A Low-cost 6D Controller with Smooth Tracking for Mobile Augmented Reality.- Chapter 9. Overview of SAR Image Change Detection.- Chapter 10. Overview of SAR Image Denoising Based on Transform Domain.- Chapter 11. An Improved Method of Non-local Means Denoising Based on Histogram.- Chapter 12. Overview of Speckle Noise Suppression Methods in SAR Image Based on NLM.- Chapter 13. Overview of SAR Image Feature Extraction and Target Recognition.- Chapter 14. Image Recognition Based on Super-resolution Wasserstein Generative Adversarial Nets with Gradient Penalty.- Chapter 15. LUCC and Landscape Pattern Variation in The Lower Tarim River By Remote Sensing.


Lakhmi C. Jain, B.E.(Hons), M.E., Ph.D., Fellow (Engineers Australia), served as Visiting Professor in Bournemouth University, UK, until July 2018 and presently serving the University of Canberra, Australia and University of Technology Sydney, Australia. Dr. Jain founded the KES International for providing a professional community the opportunities for publications, knowledge exchange, cooperation and teaming. Involving around 5,000 researchers drawn from universities and companies worldwide, KES facilitates international cooperation and generates synergy in teaching and research. KES regularly provides networking opportunities for professional community through one of the largest conferences of its kind in the area of KES.

 

Prof. Roumen Kountchev, Ph.D., D.Sc., Technical University of Sofia, Bulgaria. His scientific areas of interest are digital signal and image processing, image compression, multimedia watermarking, video communications, pattern recognition and neural networks. He has 341 papers published in magazines and conference proceedings (71 international); 15 books; 46 book chapters; 20 patents (3 international). He had been Principle Investigator of 38 research projects (6 international). He is Member of Euro Mediterranean Academy of Arts and Sciences (EMAAS), President of Bulgarian Association for Pattern Recognition (Member of Intern. Association for Pattern Recognition), Editorial Board Member of IJBST Journal Group, Member of International Research Institute for Economics and Management (IRIEM), Member of Institute of Data Science and Artificial Intelligence (IDSAI), Member of the Honorable Editorial Board of the nonprofit peer-reviewed open access IJBST Journal Group. Editorial Board Member of Intern. Journal of Reasoning-based Intelligent Systems; Intern. Journal Broad Research in Artificial Intelligence and Neuroscience; KES Focus Group on Intelligent Decision Technologies; Egyptian Computer Science Journal; Intern. Journal of Bio-Medical Informatics and e-Health; and Intern. Journal Intelligent Decision Technologies.

 Prof. Yonghang Tai is a professor at the School of Physics and Electronic Information, Yunnan Normal University, Kunming, China, Color & Image Vision Lab. He got his MSc at Yunnan Normal University, Kunming, and Ph.D. in Opto-Electronic Engineering (OE) at Deakin University, Melbourne, Australia. His main research interests are in 3D HMD design, AM-OLED drive circuit design,   and Stereoscopic imaging systems. Prof. Tai had published many journal and conference papers and has 6 patents. He took part in the Electronic Nose Designing of Tobacco Mildew Early Warning Project and Designed and debugged the AM-OLED Gamma correction system of Yunnan North OLEiD Company. Prof. Tai was the editor and reviewer of many indexed journals. He was a tutor of   MSC and PhD students who successfully defended their works.

This book presents high-quality research in the field of 3D imaging technology. The second edition of International Conference on 3D Imaging Technology (3DDIT-MSP&DL) continues the good traditions already established by the first 3DIT conference (IC3DIT2019) to provide a wide scientific forum for researchers, academia and practitioners to exchange newest ideas and recent achievements in all aspects of image processing and analysis, together with their contemporary applications. The conference proceedings are published in 2 volumes. The main topics of the papers comprise famous trends as: 3D image representation, 3D image technology, 3D images and graphics, and computing and 3D information technology. In these proceedings, special attention is paid at the 3D tensor image representation, the 3D content generation technologies, big data analysis, and also deep learning, artificial intelligence, the 3D image analysis and video understanding, the 3D virtual and augmented reality, and many related areas. The first volume contains papers in 3D image processing, transforms and technologies. The second volume is about computing and information technologies, computer images and graphics and related applications. The two volumes of the book cover a wide area of the aspects of the contemporary multidimensional imaging and the related future trends from data acquisition to real-world applications based on various techniques and theoretical approaches.



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