Google PlaNet – This artificial intelligence system goes beyond the overt to examine small clues hidden in the pixels when a certain images contain famous landmarks or unique architectures.
The program is called PlaNEt which has its geotagging abilities that are better than any other human or program and uses a deep-learning neutral network, which means the more images PlaNet sees, the smarter it gets.
According to the research team, the program is able to localize 3.6% of the images at street-level accuracy and 10.1% at city-level accuracy. 28.4% of the photos are correctly localized at country level and 48.0% at continent level,”
Researchers matched PlaNet program against 10 well-travelled people in the game”Geoguessr” to compare program’s accuracy between humans. The game provides a random street-view photo and requiring players to identify where they believe the photo was taken and played 50 rounds in total.
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As a result, PlaNet won 28 out of the 50 rounds.
The researchers trained the neural network using 29.7 million public photos from Google+. The neural network relies on clues and features from photos it has already seen to help identify the most likely whereabouts of a new image.
Nevertheless, PlaNet program has some limitations and because it only depends on internet images, the program is at a disadvantage when confronted with rural countrysides and other rarely photographed locales and the team also left out large swaths of the Earth, including oceans and the polar caps.
Tobias Weyland, the lead author on the project, noted that supplementing internet photos with satellite images resolved some of these weaknesses. PlaNet also focuses on landscapes and other factors besides landmarks, making it more accurate at identifying non-city images than other programs.