Special lssues
Table of Content

Deep Learning for Real-Time Image Enhancement

Submission Deadline: 05 September 2020 (closed)

Guest Editors

Dr. S. Balamurugan (Lead Guest Editor),Director – Research and Development, Intelligent Research Consultancy Services (iRCS), India
Dr. Bala Anand Muthu, V.R.S. College of Engineering and Technology, India
Prof. Sheng-Lung Peng, National Dong Hwa University, Hualien, Taiwan
Dr. Mohd Helmy Abd Wahab, Universiti Tun Hussein Onn Malaysia, Malaysia

Summary

The latest technological advancements have completely changed the face of real-time image processing, recognition, and enhancement. Also, the exponential growth of massive data processing and other storage requirements has made the earlier difficulties in real-time enhancement more achievable. With the rapid advancements in the areas of smart phones, wearable devices, and other satellite and surveillance systems, the image processing ability on a real-time basis has considerably increased. Besides, several techniques used to characterize and understand the real-time image enhancement, there are some difficulties related to acquiring, classifying, and segmenting the retrieved images. Sometimes the real-time image enhancing process has the possibility of pulling down the overall computing process. The incorporation of deep learning techniques in real-time image processing shall enable an insightful process that can surpass other processing and enhancing techniques.

 

For the past few years, deep learning techniques have been dominating the fields related to image processing. It provides an effective platform to study various generic features and hierarchical representations for delivering new solutions in real-time image processing. Furthermore, it has also achieved a remarkable destination in tasks like object recognition and tracking. Since the real-time image enhancement process imposes significant contribution in industries like healthcare, manufacturing, agriculture, military, and environment, the real-time image captured in any process can enhance more effectively with improved accuracy and reduced computing time. There are many deep learning algorithms like Artificial Neural Networks, Convolutional Neural Networks, and other robust image classifiers that can process the real-time images in a new dimension. With amazing benefits and progressions in implementing deep learning in real-time image enhancements, there may be some adaptability, compatibility, and other technology-related challenges in understanding image classification. However, researches in using modern deep learning models in image processing are becoming of more interest in recent times due to the advances in new science and engineering-based technologies.     

 

This special issue on Deep Learning for Real-Time Image Enhancement aims to invite researchers and professionals to contribute their original research papers that discuss ideas, theories, and methodologies along with practical examples, in implementing deep learning concepts in real-time image enhancement.

 

Suitable topics are but not limited to as follows:

• Security in a smart environment using deep learning and real-time image enhancement techniques

• Deep Learning for real-time image recognition: challenges and opportunities

• Application of Convolutional Neural Networks for real-time image enhancement

• Deep neural networks and real-time image optimization for fault detection in manufacturing industries

• Deep learning algorithms for real-time medical image enhancement

• Deep learning technique for real-time image enhancement in remote sensing

• Pattern recognition in real-time images: a deep learning perspective

• Case studies on deep learning for enhancing real-time images

• Real-time image reconstruction and enhancement using intelligent learning methodologies

• A study on real-time image compression technique using deep learning

• Future of deep learning concepts for real-time image and video processing

• An overview of design and architecture for deep learning-based real-time image enhancement



Share Link