Guest Editors
Mohit Mittal, Data Scientist, Shiratech Knowtion GmbH, Germany
Dr. Mittal is a Data Scientist at Shiratech Knowtion GmbH in Germany, with previous experience as a post-doctoral researcher at INRIA in Lille, France, starting from October 2020. Prior to that, he completed a post-doctorate at Kyoto Sangyo University in Japan, where he spent one and a half years before completing his doctorate degree at Gurukul Kangri University in India in 2018. Mohit received his Bachelor's and Master's degrees in Computer Science and Engineering from Guru Nanak Dev University in Amritsar in 2010 and 2011, respectively. He has authored numerous papers published in prestigious journals and top-tier conferences, focusing on research areas such as Wireless Sensor Networks (WSN), Natural Language Processing (NLP), Data Mining, Explainable AI, Machine Learning, and Deep Learning.
Swadha Gupta, Data Scientist, Shiratech Knowtion GmbH, Germany
Dr. Gupta is a Data Scientist at Shiratech Knowtion GmbH in Germany. She completed her doctorate degree at Thapar Institute of Engineering and Technology in India in 2023. Swadha received her Bachelor's degree in Computer Science and Engineering from Shri Mata Vaishno Devi University (SMVDU) in India in 2013 and her Master's degree from Chandigarh University India in 2015. She has authored numerous papers published in prestigious journals and top-tier conferences, focusing on research areas such as face recognition, Online learning, Machine Learning, and Deep Learning.
Deepika Koundal, Associate Professor, University of Petroleum & Energy Studies, India
Deepika Koundal is currently associated with University of Petroleum and Energy Studies, Dehradun. She received the recognition and honorary membership from Neutrosophic Science Association from University of Mexico, USA. She is also selected as a Young scientist in 6th BRICS Conclave in 2021. She received the Master and Ph.D. degrees in computer science & engineering from the Panjab University, Chandigarh in 2015. She received the B. Tech. degree in computer science & engineering from Kurkushetra University, India. She is the awardee of research excellence award given by Chitkara University in 2019 and by UPES in 2022. She has published more than 40 research articles in reputed SCI and Scopus indexed journals, conferences, and two books. She is currently a guest editor in Computers & Electrical Engineering, Internet of Things Journals (Elsevier) and IEEE Transaction of Industrial Informatics, Computational and Mathematical Methods in Medicine, MDPI Sensor, Hindawi and CMC. She is also serving as Associate Editor in Heliyon, IET Image Processing and International Journal of Computer Applications. She also has served on many technical program committees as well as organizing committees and invited to give guest lectures and tutorials in Faculty development programs, international conferences, and summer schools. Her Areas of Interest are Artificial Intelligence, Biomedical Imaging and Signals, Image Processing, Soft Computing, Machine Learning/ Deep Learning.
Summary
This special issue provides a unique space to present and discuss the cutting-edge developments in computer vision propelled by the transformative capabilities of deep learning, with a specific focus on applications related to vibrations. We eagerly welcome submissions of both comprehensive and concise papers, as well as innovative idea papers, shedding light on the latest methodologies and practical applications at the intersection of computer vision, deep learning, and the study of vibrations.
Furthermore, we look forward to captivating demonstrations and insightful posters that showcase collaborative efforts between academia and industries exploring the frontiers of visual intelligence in the realm of vibrations.
The topics of interest for this special issue include, but are not limited to:
-Advanced approaches in deep learning for computer vision applied to the analysis of vibrations
-Novel applications of deep learning in visual recognition and understanding for vibration-related studies
-Ethical considerations in deploying deep learning models for visual enhancements in vibration analysis
-Industry-specific solutions leveraging deep learning for the creation of immersive visualizations in vibration studies
-Enhancing user experience in AI-assisted solutions for vibration analysis through computer vision
-Exploring the role of data and decision bias in deep learning applications for vibrations
Join us in this collaborative exploration, where the fields of computer vision, deep learning, and vibrations intersect. Your contributions are integral to advancing our understanding and driving progress in these dynamic and interconnected domains.
Keywords
vibration; computer vision; deep learning; visual intelligence
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