scholarly journals Fined: Fast Inference Network for Edge Detection

Author(s):  
Jan Kristanto Wibisono ◽  
Hsueh-Ming Hang
Author(s):  
Michael K. Kundmann ◽  
Ondrej L. Krivanek

Parallel detection has greatly improved the elemental detection sensitivities attainable with EELS. An important element of this advance has been the development of differencing techniques which circumvent limitations imposed by the channel-to-channel gain variation of parallel detectors. The gain variation problem is particularly severe for detection of the subtle post-threshold structure comprising the EXELFS signal. Although correction techniques such as gain averaging or normalization can yield useful EXELFS signals, these are not ideal solutions. The former is a partial throwback to serial detection and the latter can only achieve partial correction because of detector cell inhomogeneities. We consider here the feasibility of using the difference method to efficiently and accurately measure the EXELFS signal.An important distinction between the edge-detection and EXELFS cases lies in the energy-space periodicities which comprise the two signals. Edge detection involves the near-edge structure and its well-defined, shortperiod (5-10 eV) oscillations. On the other hand, EXELFS has continuously changing long-period oscillations (∼10-100 eV).


2008 ◽  
Vol 128 (7) ◽  
pp. 1185-1190 ◽  
Author(s):  
Kuniaki Fujimoto ◽  
Hirofumi Sasaki ◽  
Mitsutoshi Yahara
Keyword(s):  

2014 ◽  
Vol 9 (5) ◽  
pp. 1060
Author(s):  
Frank Zoko Ble ◽  
Matti Lehtonen ◽  
Ari Sihvola ◽  
Charles Kim

2017 ◽  
Author(s):  
Prof. S. H. Jawale ◽  
Prof. A. B. Bavaskar
Keyword(s):  

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