We cordially invite researchers and scientists working in hyperspectral
image analysis all around the globe to participate and submit their
research work to contribute to our book titled "Computational
Intelligence based Hyperspectral Image Analysis".
It would help if you could let us know the tentative title of your
contribution within 10 days of receiving this mail so that we can plan /
structure the table of contents of the book.
Submission link: https://forms.gle/owMZQys1yd6zXtkMA [1]
Scope of the Book:
--------------------
Computational Intelligence (CI) based hyperspectral image analysis has
gained significant importance in recent years due to its ability to
extract valuable information from hyperspectral images and make
predictions. Hyperspectral images provide a rich source of information
about the composition and properties of objects in the environment.
However, the vast amount of data generated by hyperspectral images can
be overwhelming and hard to analyze. With their ability to provide
valuable insights and improve decision-making, Computational
Intelligence techniques act as a powerful tool that aids in automatic
analysis and improves accuracy. Recent advances in the field have
provided new and exciting ways to employ CI-based hyperspectral image
analysis in many diverse applications.
The book aims to showcase these latest achievements and novel approaches
in this field, focusing on their wide applications in agriculture, the
environment, defense, medical diagnostics, food and product inspection,
and mineral exploration. It will be an essential resource for those
seeking to deepen their understanding of how hyperspectral image
analysis can combine with computational intelligence techniques to solve
specific tasks in different application fields from a multidisciplinary
perspective.
The topics include, but are not limited to:
---------------------------------------------
Hyperspectral Image Acquisition
Hyperspectral Image Enhancement
Hyperspectral Image Clustering
Hyperspectral Image Representation
Hyperspectral Image Restoration
Hyperspectral Image Filtering
Hyperspectral Image Classification
Hyperspectral Image Segmentation
Hyperspectral Image Retrieval and Indexing
Hyperspectral Image Compression
Spatial/Spectral Super-Resolution
Computational Imaging
Object Detection
Applications in Remote Sensing
Multispectral/Hyperspectral Image Processing: Band Selection,
Dimensionality Reduction, Compressive Sensing,
Sparse Representation, Image Registration/Matching, Image
Denoising/Destriping, Image Fusion/Pansharpening
Unsupervised Learning, Semi-supervised Learning, Transfer Learning, Deep
Learning on Hyperspectral Images
Real time Monitoring and applications
Important Dates:
---------------------
Full Chapter Submission Deadline August 30, 2023
Final Notification of Acceptance October 15, 2023
Final Chapter Submission Deadline November 15, 2023
Publisher Details:
----------------------
This book will be published in the Springer Series "Intelligent Systems
Reference Library" (Electronic ISSN: 1868-4408, Print ISSN: 1868-4394)
Indexed by: SCOPUS, SCImago, DBLP, zbMATH, Norwegian Register for
Scientific Journals and Series
Submission Guidelines:
----------------------
The length of a book chapter should be between 20 and 30 pages.
Chapters must be formatted according to Springer format (Latex or Word).
The manuscript should be submitted in Word or Latex files.
The plagiarism rate should be less than 15%.
The figure should not have any copyright issues; either it can be
redrawn or a copyright certificate should be obtained.
There is no processing or publication charge for this book.
More details on https://sites.google.com/view/cihia2023/home [2]
-----
Best Regards
Editors:
Ajith Abraham, Flame University, Pune, India; Machine Intelligence
Research Labs (MIR Labs), USA
Anu Bajaj, Thapar Institute of Engineering and Technology, Patiala,
Punjab, India
Jyoti Maggu, Thapar Institute of Engineering and Technology, Patiala,
Punjab, India
Information contact: Anu Bajaj (er.anubajaj@gmail.com)
Thanks & Regards
Dr. Anu Bajaj, PDF (MIR Labs, USA)
Assistant Professor
Computer Science and Engineering Department
Thapar Institute of Engineering and Technology, Patiala, India
Internship Manager-MIR Labs, USA (http://www.mirlabs.org)
Email: anu.bajaj@mirlabs.org, er.anubajaj@gmail.com
ORCID: https://orcid.org/0000-0001-8563-6611
LinkedIn: https://www.linkedin.com/in/anu-bajaj/
Publons: https://publons.com/researcher/2918012/anu-bajaj/
Research Gate: https://www.researchgate.net/profile/Anu-Bajaj
Scopus: https://www.scopus.com/authid/detail.uri?authorId=56825307900
Google Scholar:
https://scholar.google.com/citations?user=En_N0VoAAAAJ&hl=en
Links:
------
[1] https://forms.gle/owMZQys1yd6zXtkMA
[2] https://sites.google.com/view/cihia2023/home
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