Guest Editors
Dr. Nitin Mittal, Chandigarh University, India.
Dr. Amit Kant Pandit, Shri Mata Vaishno Devi University, J&K, India.
Dr. Diego Oliva, Universidad de Guadalajara, Mexico.
Dr. Simrandeep Singh, Chandigarh University, India.
Summary
Nowadays the use of digital images and videos has been extended to different fields as surveillance, manufacturing, medicine, agriculture, machine/robot vision, pattern recognition etc. They are easy to obtain from various environments, and it is necessary to recognize the objects contained in the scenes. In order to achieve this goal, several computational approaches have been developed However, considering the technological advances problems as image size, noise, illumination and security, it is necessary to develop new methodologies and to improve the classical algorithms. On the other hand, a tendency is that the computer vision and image processing systems should be able to automatic extract the desired features for a particular task. Computational Intelligence (CI) approaches are alternative solutions for automatic computer vision and image processing systems; they include the use of tools as machine learning and soft computing. Researchers from all over the world are working hard creating new algorithms that combine the methods provided by CI approaches to solve the problems of image processing and computer vision.
This proposal aims to provide a collection of high-quality research works that address broad challenges in both theoretical and application aspects of soft computing and machine learning in image processing and computer vision. We invite researchers and colleagues to contribute original work that will stimulate the continuing effort on the application of CI approaches to solve image-processing and computer vision problems.
We invite all researchers and practitioners who are developing algorithms, systems, and applications, to share their results, ideas, and experiences.
Topics of interest include, but are not limited to, the following:
· Computer vision based mobile applications and clinical information assessment
· Automated agricultural growth mapping and crop yield production
· Fog Vision Enhancement and applications
· Healthcare, Automotive, Robotics, Surveillance and Remote Sensing through imaging
· Colour compensation and enhancement of underwater images
· Multi-temporal, multi-modal and multi-focus image fusion
· Pharmaceutical automated inspection and sorting
· Optical character recognition and pattern recognition
· Blob detection, extraction and image matching
· Robust image representation for scalable visual retrieval and recognition
· Futuristic biomedical analysis through hybrid techniques
· Computer aided Analysis in oncology and radiology
· Hybrid intelligent systems in Biometric Recognition
· Recent trends for low dose radiation imaging
· Efficient algorithms in Super-resolution imaging
· Artificial Intelligence: Knowledge representation and Reasoning
· Machine learning in healthcare systems
· Deep learning for sensor dependent activity recognition
· Advances in graph-based representation in pattern recognition
· Application of Internet of things for implicit Biometric authentication and monitoring
· Multimedia analysis, computer vision, natural language processing for visual question answering
· Imaging in Digital Industrial Forensics and Bio cybernetics
· Ambient assistive living using artificial intelligence and imaging
Keywords
Image segmentation
Bio medical Images
Meta heuristic
Machine Vision
Pattern recognition
Image Fusion
Image De noising
Image Enhancement
Satellite images
Soft computing
Published Papers
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