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The Convergence of Deep Learning and Computer Vision: Smart City Applications and Research Challenges

Deep Kothadiya, Aayushi Chaudhari, Ruchita Macwan, Krishna Patel, Chintan Bhatt

2021Atlantis Highlights in Computer Sciences/Atlantis highlights in computer sciences21 citationsDOIOpen Access PDF

Abstract

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.

Topics & Concepts

Convergence (economics)Computer scienceArtificial intelligenceDeep learningHuman–computer interactionEconomic growthEconomicsVideo Surveillance and Tracking MethodsRemote-Sensing Image ClassificationCOVID-19 diagnosis using AI
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