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Maskinrummet vid Arboga Margarinfabrik. (Bilden ingår i ett fotoalbum med rubriken - Aktiebolaget Arboga margarinfabrik).
Packrum vid Arboga Margarinfabrik. (Bilden ingår i ett fotoalbum med rubriken - Aktiebolaget Arboga margarinfabrik).
Konstistertillverkning vid Arboga Margarinfabrik AB.
Flygfoto över Arboga margarinfabriken, Arboga.Tagen av Ahrenbergsflyg.
Exteriör av smedja och stall vid Arboga Margarinfabrik AB.
Interiör av matsal vid Arboga Margarinfabrik AB.
Arboga Margarinfabrik. En liten lastbil står parkerad intill husväggen.
Arboga Margarinfabrik, interiör. Man vid maskin.Mannen heter Harald Johansson. Denna bild finns med i Reinhold Carlssons bok Arboga objektivt sett.Läs mer om Arboga Margarinfabrik i Arboga Minnes årsbok 1978.
Aktiebolaget Upsala Margarinfabrik. Fabriksgården med en av lastbilarna på väg till järnvägsstationen.
Utlastning vid Arboga Margarinfabrik. (Bilden ingår i ett fotoalbum med rubriken - Aktiebolaget Arboga margarinfabrik).
Summary
Utlastning vid Arboga Margarinfabrik. (Bilden ingår i ett fotoalbum med rubriken - Aktiebolaget Arboga margarinfabrik).
The train station image dataset is picked from the world's largest public domain archive. Made in two steps - first, curated set, followed by running 25 Million public domain images through image recognition, it comprises more than 50,000 train station images from all countries and times. All images are in the public domain, so there are no restrictions on the dataset usage - educational, scientific, and commercial.
We at GetArchive are exploring new methods of image metadata augmentation and verification. Our goal is to make it possible to find images on any topic. In particular, we are trying to verify and fix historic periodization. This collection is made of historic photographs of automobiles that look as if they were taken in the 1940s. The collection is made with aid of a neural image recognition network dealing with the whole image composition rather than with the car model - some cars may be dated incorrectly. Although, while this method is surprisingly good for the purpose of dating and tagging, a certain percentage of images (less than 8%) may not represent automobile, but other vehicle type or visually similar object. Naturally, our next step should be creating numerous datasets for a particular car years&models, but as of September 2022, we found no use to justify the effort.