21,272 research outputs found
Uneven illumination surface defects inspection based on convolutional neural network
Surface defect inspection based on machine vision is often affected by uneven
illumination. In order to improve the inspection rate of surface defects
inspection under uneven illumination condition, this paper proposes a method
for detecting surface image defects based on convolutional neural network,
which is based on the adjustment of convolutional neural networks, training
parameters, changing the structure of the network, to achieve the purpose of
accurately identifying various defects. Experimental on defect inspection of
copper strip and steel images shows that the convolutional neural network can
automatically learn features without preprocessing the image, and correct
identification of various types of image defects affected by uneven
illumination, thus overcoming the drawbacks of traditional machine vision
inspection methods under uneven illumination
Diphoton excess at 750 GeV: gluon-gluon fusion or quark-antiquark annihilation?
Recently, ATLAS and CMS collaboration reported an excess in the diphoton
events, which can be explained by a new resonance with mass around 750 GeV. In
this work, we explored the possibility of identifying if the hypothetical new
resonance is produced through gluon-gluon fusion or quark-antiquark
annihilation, or tagging the beam. Three different observables for beam
tagging, namely the rapidity and transverse momentum distribution of the
diphoton, and one tagged bottom-jet cross section, are proposed. Combining the
information gained from these observables, a clear distinction of the
production mechanism for the diphoton resonance is promising.Comment: 20 pages, 7 figure
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