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Annotated birds dataset for object detection using deep learning, Skagen & Klim

SND-ID: 2021-316

Creator/Principal investigator(s)

Hiba Alqaysi - Mid Sweden University

Description

The two datasets are of image frames of birds collected in two sites in Denmark, namely Skagen and Klim. Each image frame has its corresponding text file that contains the coordinates of bounding boxes containing the objects. The datasets are used in the following publication: "A Temporal Boosted YOLO-Based Model for Birds Detection around Wind Farms". The publication should be referenced when using the dataset by other researchers.

The datasets were collected at two sites in Denmark over the course of a few months in 2017 and 2018. They were manually annotated using the freely available LabelImg online tool. The Skagen dataset was collected at the Skagen Grey Lighthouse, Center of Migratory Birds using a pair of wide-angle, monochrome cameras firmly affixed to rigid boxes. The Kilm set was collected at Klim Fjordeholme using the same camera setup; except the cameras were mounted on tripods.

Language

English

Research principal, contributors, and funding

Research principal

Mid Sweden University

Responsible department/unit

Department of Electronics Design (EKS)

Contributor(s)

Igor Fedorov - Linköping University

Funding

  • Funding agency: Knowledge foundation
Protection and ethical review

Data contains personal data

No

Method and time period
Geographic coverage

Geographic spread

Geographic location: Denmark

Geographic description: Two wind farms in Denmark, namely Skagen - Grey Lighthouse and Klim Fjordeholme

Topic and keywords

Research area

Computer Vision and Robotics (Autonomous Systems) (The Swedish standard of fields of research 2011)

Keywords

yolov4, sky surveillance, object detection

Publications

Alqaysi, H., Fedorov, I., Qureshi, Faisal. Z., & O’Nils, M. (2021). A temporal boosted yolo-based model for birds detection around wind farms. In Journal of Imaging (No. 227; Vol. 7, Issue 11). https://doi.org/10.3390/jimaging7110227
URN: urn:nbn:se:miun:diva-43641
DOI: https://doi.org/10.3390/jimaging7110227

If you have published anything based on these data, please notify us with a reference to your publication(s). If you are responsible for the catalogue entry, you can update the metadata/data description in DORIS.

Dataset
Annotated birds datasets for object detection using deep learning, Skagen and Klim

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Associated documentation

Description

The datasets were collected at two sites in Denmark over the course of a few months in 2017 and 2018. The datasets were manually annotated using the freely available LabelImg online tool. The Skagen dataset was collected at the Skagen Grey Lighthouse, Center of Migratory Birds using a pair of wide-angle, monochrome cameras firmly affixed to rigid boxes. The Kilm data were collected at Klim Fjordeholme using the same camera setup; except, here, the cameras are mounted on tripods.

Version 1

Citation

Hiba Alqaysi. Mid Sweden University (2021). Annotated birds datasets for object detection using deep learning, Skagen and Klim. Swedish National Data Service. Version 1. https://doi.org/10.5878/x1cm-pq40

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Data format / data structure

Text

Still image

Creator/Principal investigator(s)

Hiba Alqaysi - Mid Sweden University

Published: 2021-12-08
Last updated: 2021-12-13