TY  -  
T1  - Image Recognition for Atomic Force Microscopy 
SN  -  /  
UR  - URN:NBN:fi:hulib-202109233754; http://hdl.handle.net/10138/334559 
T3  -  
A1  - Kurki, Lauri 
A2  -  
PB  - Helsingin yliopisto 
Y1  - 2021 
LA  - eng 
AB  - Atomic force microscopy (AFM) is a widely utilized characterization method capable of capturing atomic level detail in individual organic molecules. However, an AFM image contains relatively little information about the deeper atoms in a molecule and thus interpretation of AFM images of non-planar molecules offers significant challenges for human experts. An end-to-end solution starting from an AFM imaging system ending in an automated image interpreter would be a valuable asset for all research... 
VO  -  
IS  -  
SP  -  
OP  -  
KW  - Atomic force microscopy; machine learning; deep learning; convolutional neural networks; Laskennallinen materiaalifysiikka; Computational Material Physics; Beräkningsmaterialfysik; Materiaalitutkimuksen maisteriohjelma; Master's Programme in Materials Research; Magisterprogrammet i materialforskning 
N1  -   
PP  -  
ER  -