Kavicsok jellemzőinek becslése mesterséges intelligenciával

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Cím angolul: 
Predicting pebble properties with artificial intelligence
Típus: 
BSc szakdolgozat téma - alkalmazott fizika
BSc szakdolgozat téma - fizikus
Félév: 
2020/21/2.
Témavezető: 
Név: 
Török János
Email cím: 
torok@phy.bme.hu
Intézet/Tanszék/Cégnév: 
Elméleti Fizika Tanszék
Beosztás: 
Docens
Hallgató: 
Név: 
Varga Ádám Marcell
Képzés: 
Fizika BSc - fizikus
Elvárások: 

Jó programozói kéßzség

Leírás: 

Pebbles are born as fragments in mountains and cliffs and are transported by air and water. During this transport the pebbles hit each other and the riverbed or big rocks which results in the evolution of their shape. This erosion process which can displace cliffs by meters a year or destroy beaches is of big safety and economical importance. The shape of a pebble can tell how far the pebble was born or how long did it live on the beach and thus it gives valuable information about the erosion processes. Nowadays it is relatively easy to scan the form of the pebbles even in situ, thanks to advanced 3d technology and cheap measuring devices, e.g. cell phones. However, it remains the scientists' task to calculate the pebble descriptors based on its shape. These calculations are difficult and have many uncertainty and still some part of the evaluation is done by hand. The task of this thesis would be to predict the shape descriptors, e.g. number of equilibrium points, enveloping polyhedron, etc., based on the 3d stl image of the pebble. 

Titkosítas: 
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