DroneSegNet: Robust Aerial Semantic Segmentation for UAV-Based IoT Applications

Unmanned Aerial Vehicles (UAVs) are the promising "Flying IoT" devices of the future, which can be equipped with various sensors and cognitive capabilities to perform numerous tasks related to remote sensing, search and rescue operations, object tracking, segmentation of roads and building...

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Bibliographische Detailangaben
Veröffentlicht in:	IEEE transactions on vehicular technology Jg. 71; H. 4; S. 4277 - 4286
Hauptverfasser:	Chakravarthy, Anirudh S., Sinha, Soumendu, Narang, Pratik, Mandal, Murari, Chamola, Vinay, Yu, F. Richard
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.04.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	aerial scene analysis Cloud computing Coders Computer architecture Deep learning Drone aircraft Drones Feature extraction Feature maps Image segmentation Internet of Things IoT Machine learning Modules Remote sensing Remote sensors Rescue operations Robustness Search and rescue missions Semantic segmentation Semantics UAVs Unmanned aerial vehicles
ISSN:	0018-9545, 1939-9359
Online-Zugang:	Volltext
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