20 августа 2020

Форма участия: Дистанционная

Срок подачи заявок: 15 мая 2020

Индексирование сборника: Scopus, Springer

Организаторы: Anand Deshpande, Vania V. Estrela, Prashant Patavardhan

Контактное лицо: Anand Deshpande

email: deshpande.anandb@gmail.com

Super-Resolution (SR) techniques can be used in general image processing, microscopy, security, biomedical imaging, automation/robotics, biometrics among other areas to handle the dimensionality conundrum posed by the conflicts caused by the necessity to balance image acquisition, image modality/resolution/representation, subspace decomposition, compressed sensing, and communications constraints. Lighter computational implementations are needed to circumvent the heavy computational burden brought in by SR image processing applications. Soft computing and, specifically, Deep Learning (DL) ascend as possible solutions to SR efficient deployment. The amount of multi-resolution and multimodal images has been augmenting the need for more efficient and intelligent analyses, for example, computer-aided diagnosis via Computational Intelligence (CI) techniques.

The intend of publishing the book is to serve for researchers, technology professionals, academicians and students working in the area of latest advances and upcoming technologies employing CI methods for SR in imaging processing applications. This book explores the application of deep learning techniques within a particularly difficult computational type of computer vision problem: SR. This book aspires to provide assortment of novel research works that focuses on broad challenges of CI approaches for SR in image processing applications.

We invite all researchers, academicians, developers and research scholars to contribute chapters in the field of CI and SR with an emphasis on practical examples. Each article is expected to cover Computational Intelligence methods for Super Resolution in image processing applications.

List of Topics

All papers must be original and not simultaneously submitted to another journal or conference. The following papers categories are welcome:

A) CI models such as:

  • Biologically-Inspired Methods
  • Fuzzy Systems
  • Metaheuristics Approaches
  • Multi-Agent Strategies
  • Statistical Methods
  • Gaussian Mixture Models
  • Bayesian Models
  • Markov Methods
  • Projections onto Convex Sets (POCS) aka Alternating-Projection Methods
  • Soft Computing
  • Machine Learning
  • Rough Sets
  • Radial Basis Functions
  • Deep Coding Networks
  • Modified Artificial Neural Networks
  • Self-Belief Neural Networks
  • Spiking Neural Networks
  • Large Memory Storage and Neural Retrieval Networks
  • Deep Q-Networks
  • Deep Stacking Networks
  • Convolutional Neural Networks
  • Reinforcement Learning Networks
  • Extreme Learning Machine (ELM)
  • Hybrid Methods
  • CI Software
  • CI-Dedicated Hardware
  • Other CI paradigms

(B) Image Processing

  • Recognition of less constrained face, iris, ear, fingerprints, gait, DNA, etc.
  • SR in Different Color Spaces
  • Dimensionality Curse and SR
  • Image Enhancement/De-Hazing/In-Painting/Compression
  • Image Restoration/Registration/Fusion/Annotation
  • Multimodality Image Processing and Rendering
  • Remote Sensing
  • Robotics and Automation
  • Real-Time Image Processing
  • 3D Vehicle Navigation
  • Microscopy
  • Video and Multimedia
  • Content-Based Retrieval for Image, Video, Multimedia, Multimodality
  • Satellite Image Analysis
  • Multi-resolution, Multispectral and Hyperspectral imaging
  • Biomedical Imaging
  • Healthcare, Surgery, and Telemedicine
  • Educational Tools
  • Assistive Computing Living
  • SR in Cloud Computing, Distributed Computing, and Mobile Edge Cloud
  • Biosensors, Bioactuators and Smart Devices
  • Dynamic Super-Resolution
  • 3D-4D Image Processing
  • Security
  • Data Visualization
  • Virtual and Augmented Reality
  • Other cutting-edge image processing areas

** Paper submissions are expected to cover at least one topic from List A and at least one from List B.


CISRI 2020 Book Chapters will be published in SCOPUS Indexed Springer Nature Book

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