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Deep Learning articles use benchmarks to measure the quality of the results. However, several benchmarks do not have the copyright of all data used. So, how to believe that every paper uses the same benchmark?
From https://www.go-fair.org/fair-principles/ we have the description of the FAIR acronym
From the article Implementing FAIR Data Principles: The Role of Libraries (https://libereurope.eu/wp-content/uploads/2017/12/LIBER-FAIR-Data.pdf) we include the following additional description on the Reusable term: Data and collections have a clear usage licenses and provide accurate information on provenance.
Top-3 dataset for Deep Learning, based on a 25 list (https://www.analyticsvidhya.com/blog/2018/03/comprehensive-collection-deep-learning-datasets/)
Follow my podcast: http://anchor.fm/tkorting
Subscribe to my YouTube channel: http://youtube.com/tkorting
The intro and the final sounds were recorded at my home, using an old clock that belonged to my grandmother.
Thanks for listening
By ThalesDeep Learning articles use benchmarks to measure the quality of the results. However, several benchmarks do not have the copyright of all data used. So, how to believe that every paper uses the same benchmark?
From https://www.go-fair.org/fair-principles/ we have the description of the FAIR acronym
From the article Implementing FAIR Data Principles: The Role of Libraries (https://libereurope.eu/wp-content/uploads/2017/12/LIBER-FAIR-Data.pdf) we include the following additional description on the Reusable term: Data and collections have a clear usage licenses and provide accurate information on provenance.
Top-3 dataset for Deep Learning, based on a 25 list (https://www.analyticsvidhya.com/blog/2018/03/comprehensive-collection-deep-learning-datasets/)
Follow my podcast: http://anchor.fm/tkorting
Subscribe to my YouTube channel: http://youtube.com/tkorting
The intro and the final sounds were recorded at my home, using an old clock that belonged to my grandmother.
Thanks for listening