English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

The widespread popularity of unmanned aerial vehicles enables an immenseamount of power lines inspection data to be collected. How to employ massiveinspection data especially the visible images to maintain the reliability,safety, and sustainability of power transmission is a pressing issue. To date,substantial works have been conducted on the analysis of power lines inspectiondata. With the aim of providing a comprehensive overview for researchers whoare interested in developing a deep-learning-based analysis system for powerlines inspection data, this paper conducts a thorough review of the currentliterature and identifies the challenges for future research. Following thetypical procedure of inspection data analysis, we categorize current works inthis area into component detection and fault diagnosis. For each aspect, thetechniques and methodologies adopted in the literature are summarized. Somevaluable information is also included such as data description and methodperformance. Further, an in-depth discussion of existing deep-learning-relatedanalysis methods in power lines inspection is proposed. Finally, we concludethe paper with several research trends for the future of this area, such asdata quality problems, small object detection, embedded application, andevaluation baseline.

Review of data analysis in vision inspection of power lines with an in-depth discussion of deep learning technology