The Convergence of Deep Learning and Computer Vision: Smart City Applications and Research Challenges
- 10.2991/ahis.k.210913.003How to use a DOI?
- Agriculture, Computer Vision, Deep Learning, Healthcare, Smart City, Transportation, Video Surveillance
In recent years, deep learning strategies started to outshine traditional machine learning methods in a few fields, with Computer Vision being one of the most noticeable ones. The Computer Vision is becoming more suitable nowadays at identifying patterns from images than the human visual cognitive system. It ranges from raw information recording to methods and ideas that span digital image processing, machine learning, and computer graphics. The wide utilization of Computer Vision has attracted many researchers to incorporate their ideas with different fields and disciplines. The era of smart cities has emerged to meet the recent demands of citizens using information and communication technology. This paper reviews research efforts that utilize Deep Learning Frameworks and Computer Vision Applications in support of smart city applications like smart healthcare, smart transportation, smart agriculture, etc. Furthermore, the paper identified key research challenges that emanate from the use of deep learning and computer vision in support of smart city services.
- © 2021, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Deep Kothadiya AU - Aayushi Chaudhari AU - Ruchita Macwan AU - Krishna Patel AU - Chintan Bhatt PY - 2021 DA - 2021/09/13 TI - The Convergence of Deep Learning and Computer Vision: Smart City Applications and Research Challenges BT - Proceedings of the 3rd International Conference on Integrated Intelligent Computing Communication & Security (ICIIC 2021) PB - Atlantis Press SP - 14 EP - 22 SN - 2589-4900 UR - https://doi.org/10.2991/ahis.k.210913.003 DO - 10.2991/ahis.k.210913.003 ID - Kothadiya2021 ER -