Report Open Access

Deep Learning on Imaging Calorimetry

Mahapatra, Jayesh; Pierini, Maurizio; Vlimant, Jean-Roch; Spiropulu, Maria


MARC21 XML Export

<?xml version='1.0' encoding='UTF-8'?>
<record xmlns="http://www.loc.gov/MARC21/slim">
  <leader>00000nam##2200000uu#4500</leader>
  <datafield tag="653" ind1=" " ind2=" ">
    <subfield code="a">CERN openlab summer student</subfield>
  </datafield>
  <controlfield tag="005">20190410035326.0</controlfield>
  <controlfield tag="001">208488</controlfield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="u">Summer Student Supervisor</subfield>
    <subfield code="a">Pierini, Maurizio</subfield>
  </datafield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="u">Summer Student Supervisor</subfield>
    <subfield code="a">Vlimant, Jean-Roch</subfield>
  </datafield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="u">Summer Student Supervisor</subfield>
    <subfield code="a">Spiropulu, Maria</subfield>
  </datafield>
  <datafield tag="856" ind1="4" ind2=" ">
    <subfield code="s">1745161</subfield>
    <subfield code="z">md5:53fa4428e58a82f64c7fb256befa9aff</subfield>
    <subfield code="u">https://zenodo.org/record/208488/files/Jayesh_openlab_report.pdf</subfield>
  </datafield>
  <datafield tag="542" ind1=" " ind2=" ">
    <subfield code="l">open</subfield>
  </datafield>
  <datafield tag="260" ind1=" " ind2=" ">
    <subfield code="c">2016-12-19</subfield>
  </datafield>
  <datafield tag="909" ind1="C" ind2="O">
    <subfield code="p">openaire</subfield>
    <subfield code="p">user-cernopenlab</subfield>
    <subfield code="o">oai:zenodo.org:208488</subfield>
  </datafield>
  <datafield tag="100" ind1=" " ind2=" ">
    <subfield code="u">CERN openlab Summer Student</subfield>
    <subfield code="a">Mahapatra, Jayesh</subfield>
  </datafield>
  <datafield tag="245" ind1=" " ind2=" ">
    <subfield code="a">Deep Learning on Imaging Calorimetry</subfield>
  </datafield>
  <datafield tag="980" ind1=" " ind2=" ">
    <subfield code="a">user-cernopenlab</subfield>
  </datafield>
  <datafield tag="540" ind1=" " ind2=" ">
    <subfield code="u">http://creativecommons.org/licenses/by/4.0/legalcode</subfield>
    <subfield code="a">Creative Commons Attribution 4.0 International</subfield>
  </datafield>
  <datafield tag="650" ind1="1" ind2="7">
    <subfield code="a">cc-by</subfield>
    <subfield code="2">opendefinition.org</subfield>
  </datafield>
  <datafield tag="520" ind1=" " ind2=" ">
    <subfield code="a">&lt;p&gt;Abstract&lt;/p&gt;

&lt;p&gt;Particle reconstruction is a significant task in analysis of CMS data. Currently physics based algorithms in conjunction with CMS readouts are used. In this project we explored deep learning as a technique for photon identification and reconstruction on the public LCD CaloImage dataset. Several network architectures were tested for performing classification (photon vs pion discrimination) and regression analysis of energy of particle hits. The performance of the topologies were plotted and compared.&lt;/p&gt;</subfield>
  </datafield>
  <datafield tag="024" ind1=" " ind2=" ">
    <subfield code="a">10.5281/zenodo.208488</subfield>
    <subfield code="2">doi</subfield>
  </datafield>
  <datafield tag="980" ind1=" " ind2=" ">
    <subfield code="a">publication</subfield>
    <subfield code="b">report</subfield>
  </datafield>
</record>
142
55
views
downloads
All versions This version
Views 142142
Downloads 5555
Data volume 96.0 MB96.0 MB
Unique views 134134
Unique downloads 5252

Share

Cite as