000002808 001__ 2808
000002808 005__ 20211231160051.0
000002808 037__ $$aBELLE2-MTHESIS-2021-081
000002808 041__ $$aeng
000002808 100__ $$aJohannes Bilk
000002808 245__ $$aEmploying Deep Learning to Find Slow Pions in the Pixel Detector in the Belle II Experiment
000002808 260__ $$aGiessen$$bII. Institute of Physics$$c2021
000002808 300__ $$amult. p
000002808 500__ $$aPresented on 25 11 2021
000002808 502__ $$aMSc$$bGiessen, Justus-Liebig-University$$c2021
000002808 520__ $$aSlow pions (pT<230 MeV/c) are detected and classified based exclisively upon their cluster shape in the PXD, using a neural network (NN) performing image processing. Input to the NN is a 9x9 pixel matrix. ADC values are encoded as grayscale values. The NN uses convolution to encode neighborhood relations in the pixel data. 78% efficiency ("precision") of correct pion identification and 79% rejection of background is achieved.  
000002808 700__ $$aJens Sören Lange$$edir.
000002808 8560_ $$fsoerenlange@yahoo.com
000002808 8564_ $$uhttps://docs.belle2.org/record/2808/files/BELLE2-MTHESIS-2021-081.pdf
000002808 980__ $$aTHESIS