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Real-Time On-Board Deep Learning Fault Detection for Autonomous UAV Inspections
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Automatic autonomous vision-based power line inspection: A review of current status and the potential role of deep learning
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inferredcites →https://doi.org/10.1109/icip.2016.7532456openalex-snapshot
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inferredcites →https://doi.org/10.1109/icstcc.2019.8885596openalex-snapshot
Development of UAV System for Autonomous Power Line Inspection
inferredcites →https://doi.org/10.1109/ipdpsw.2018.00091openalex-snapshot
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Vision-Based Novelty Detection Using Deep Features and Evolved Novelty Filters for Specific Robotic Exploration and Inspection Tasks
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Real-time On-board Detection of Components and Faults in an Autonomous UAV System for Power Line Inspection
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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DEEP LEARNING TO SUPPORT 3D MAPPING CAPABILITIES OF A PORTABLE VSLAM-BASED SYSTEM
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