IEEE Consumer Electronics Magazine · 2019 · 67 citations · 13 references
ComputingAutonomous SystemsComputer ScienceArtificial IntelligenceComputer VisionTransportationIntelligent Transportation SystemsObject RecognitionPattern RecognitionTraffic EngineeringConvolutional Neural NetworksRescueRoad RageTraffic CongestionTraffic ManagementTraffic Monitoring Systems
Unmanned aerial vehicles (UAVs) are gradually becoming useful and common. In the consumer electronics (CE) category, unmanned systems have changed the way monitoring by air is conducted in such fields as transportation, the environment, and emergency rescue. This article examines how UAVs combined with artificial-intelligence (AI) technology are used for recognizing traffic congestion. Congested roadways cause traffic delays, which wastes fuel, adds to pollution, and invites road rage. Society can benefit from technologies that help recognize and relieve traffic congestion. We present a practical framework for using UAVs to recognize traffic problems. According to this framework, images of traffic scenes are first captured by a UAV system based on route-planning technology. Then the aerial images are further processed by using convolutional neural networks (CNNs). Finally, the output is transferred to a traffic management center.
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Deep Residual Learning for Image Recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren et al. · 2016 · 222.1K citations · Full text
ImageNet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher et al. · 2009 IEEE Conference on Computer Vision and Pattern Recognition · 2009 · 61.8K citations
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
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Engineering, Computer Engineering, Electrical Engineering +16