Research

We believe in Open Source and sharing with the community.

To monitor the Open Innovation activity of corporates, several of our Machine Learning (ML) Algorithms are built to recognize the logos of companies.

During the process of creating these algorithms, we used a lot of papers from the research community to increase the accuracy of our algorithms. This is the reason we want to give back to this particular community, the researchers focussing on Machine Learning.

To 'train' a ML algorithm to recognize and classify the logos you need to give it a dataset with logos to train on. We created an immense dataset and we are willing to make this dataset accessible to support and increase the knowledge regarding Machine Learning.

Do you want more information regarding Logo Recognition, please read our blog: https://inforintelligence.com/blog/2_dataset_opensource/

Information regarding the dataset:

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 'InForIntelligence Logos 29 Dataset' | 29 classes | | Banks around the World | |Raw Logo Images|

ABN Amro ~ 400                       Agricultural Bank of China ~ 100

BNP Paribas ~ 530                    BPCE ~ 80

BancoSantander ~ 260             Bank of America ~ 470

Bank of China ~ 200                Bank of Communications ~ 70

Barclays ~ 280                        China Construction Bank ~ 100

Credit Suisse ~ 300                Crédit Agricole ~ 450

HSBC ~ 660                            ICBC ~ 130

ING ~400                               JPMorgan Chase ~ 340

Japan Post Bank ~ 40             Lloyds Banking Group ~200

MUFJ ~ 200                            Mizuho ~ 100

Postal Savings Bank of China ~ 35  Rabobank~ 400

Royal Bank of Canada ~ 220    Société Générale ~ 200

Sumitomo ~ 80                       UBS ~ 150

Unicredit ~ 340                      Volksbank ~ 280

Wells Fargo ~ 550

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Interested in this set?