Data from "Modelling calibration uncertainty in networks of environmental sensors"
A set of (slow motion) videos of bumblebees taken around 2020. Dataset also contains a CSV file with citizen science guesses as to the species in each, guesses by a neural network and a ground truth (from an expert).
The videos (are stored in the set of zip files, to make it
easier to download/upload.
- taken using smart phones with slow motion mode.
- codec: H.264 (High Profile).
- 1280 × 720.
The CSV file contains the following headers:
> video -- the filename of the video (see in zip files)
> person 1..person 5 -- the guesses by each individual as to the species. No entry means they didn't guess for that entry.
> CNN -- the guesses by the convolutional neural network*
> ground truth -- the guess by an expert.
Most entries are either blank or the scientific name for a species. There is also 'whitebuff' -- which means that bee was either Bombus terrestris or one of the Bombus lucorum species, but are very often too difficult to distinguish in the field, so have been combined.
* For how these predictions were made, see Ollett, J. (2021) Bumblebee classiﬁcation with convolutional neural networks. Undergraduate final year dissertation, University of Sheﬃeld.
- There is no personal data or any that requires ethical approval
- The data complies with the institution and funders' policies on access and sharing
Sharing and access restrictions
- The data can be shared openly
- The file formats are open or commonly used
Methodology, headings and units
- Headings and units are explained in the files