[ page under development ]
Who used Brainwash Dataset?
This bar chart presents a ranking of the top countries where dataset citations originated. Mouse over individual columns to see yearly totals. These charts show at most the top 10 countries.
Biometric Trade Routes
To help understand how Brainwash Dataset has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Brainwash Dataset was collected, verified, and geocoded to show the biometric trade routes of people appearing in the images. Click on the markers to reveal research projects at that location.
- Academic
- Commercial
- Military / Government
Citation data is collected using
SemanticScholar.org then dataset usage verified and geolocated.
Dataset Citations
The dataset citations used in the visualizations were collected from Semantic Scholar, a website which aggregates and indexes research papers. Each citation was geocoded using names of institutions found in the PDF front matter, or as listed on other resources. These papers have been manually verified to show that researchers downloaded and used the dataset to train or test machine learning algorithms.
(ignore) research notes
- The VGG Face 2 dataset includes approximately 1,331 actresses, 139 presidents, 16 wives, 3 husbands, 2 snooker player, and 1 guru
- The original VGGF2 name list has been updated with the results returned from Google Knowledge
- Names with a similarity score greater than 0.75 where automatically updated. Scores computed using
import difflib; seq = difflib.SequenceMatcher(a=a.lower(), b=b.lower()); score = seq.ratio()
- The 97 names with a score of 0.75 or lower were manually reviewed and includes name changes validating using Wikipedia.org results for names such as "Bruce Jenner" to "Caitlyn Jenner", spousal last-name changes, and discretionary changes to improve search results such as combining nicknames with full name when appropriate, for example changing "Aleksandar Petrović" to "Aleksandar 'Aco' Petrović" and minor changes such as "Mohammad Ali" to "Muhammad Ali"
- The 'Description' text was automatically added when the Knowledge Graph score was greater than 250
TODO
- create name list, and populate with Knowledge graph information like LFW
- make list of interesting number stats, by the numbers
- make list of interesting important facts
- write intro abstract
- write analysis of usage
- find examples, citations, and screenshots of useage
- find list of companies using it for table
- create montages of the dataset, like LFW
- create right to removal information