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

SND-ID: 2021-316-1. Version: 1. DOI: https://doi.org/10.5878/x1cm-pq40

Citation

Creator/Principal investigator(s)

Hiba Alqaysi - Mid Sweden University

Research principal

Mid Sweden University - Department of Electronics Design (EKS) rorId

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.

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 dat

... Show more..
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.

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. Show less..

Data contains personal data

No

Language

Method and outcome

Data format / data structure

Data collection
Geographic coverage

Geographic spread

Geographic location: Denmark

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

Administrative information

Responsible department/unit

Department of Electronics Design (EKS)

Contributor(s)

Igor Fedorov - Linköping University

Funding

  • Funding agency: Knowledge foundation
Topic and keywords

Research area

Computer vision and robotics (autonomous systems) (Standard för svensk indelning av forskningsämnen 2011)

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
SwePub: oai:DiVA.org:miun-43641

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.

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