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DroNER: Dataset for drone named entity recognition

The dataset is constructed from the drone flight log messages extracted from publicly available drone image datasets provided by VTO Labs under the Drone Forensic Program. The entire process of building this dataset includes extraction, decryption, parsing, cleansing, unique filtering, annotation, s...

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Detalles Bibliográficos
Autores principales: Silalahi, Swardiantara, Ahmad, Tohari, Studiawan, Hudan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10293979/
https://www.ncbi.nlm.nih.gov/pubmed/37383784
http://dx.doi.org/10.1016/j.dib.2023.109179
Descripción
Sumario:The dataset is constructed from the drone flight log messages extracted from publicly available drone image datasets provided by VTO Labs under the Drone Forensic Program. The entire process of building this dataset includes extraction, decryption, parsing, cleansing, unique filtering, annotation, splitting, and analysis. The resulting dataset is in CoNLL format, annotated using the IOB2 scheme with six entity types. The total number of log messages acquired from 12 DJI drone models is 1850. The data are split based on the drone models, resulting in 1412 messages for training and 438 messages for testing. The average length of log messages is 6.5 globally, 6.6 and 8.8 for the train and the test sets, respectively.