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  <titleInfo>
    <title>Auto tree counting for oil palm plantation based on UAV/drone  orthophoto</title>
  </titleInfo>
  <name type="personal">
    <namePart>Eiffel Syafhamka Nadimen A/l Syamsul</namePart>
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    <dateIssued encoding="marc">2023</dateIssued>
    <copyrightDate encoding="marc">2023</copyrightDate>
    <issuance>monographic</issuance>
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  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
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  <physicalDescription>
    <extent>xii, 61 pages : illustrations ; 1 CD-ROM.</extent>
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  <abstract>Tree counting plays a crucial role in assessing the number of tree crops within a  specific area or plantation farms, and computer vision techniques using aerial or satellite  imagery have become prevalent in this domain. Currently, manual digitization is the  traditional method employed for tree counting, but it falls behind the advancements in  machine learning. To address this, a more effective approach is sought to assist plantation  owners with palm oil tree counting and land resource management for a faster and more  accurate tree counting method that can be used in ArcGIS. This study will utilize the  Faster R-CNN due to its usage of a two-stage pipeline and leverage power of deep  learning. This method was able to detect and plot the palm oil tree on the crown of each  tree but due to the average precision only being 75%, the method can only detect the trees  correctly to a certain extent. Also, the transformation of georeferencing plot points for all  the tree using an affine transformation coefficient causes the output to not be aligned in  its correct position when outputted into ArcGIS. With that the deployment of Faster RCNN method for palm oil tree counting has been successful, demonstrating its ability to  offer a faster and more efficient alternative to manual digitize but the integration of output  into ArcGIS software poses as a challenge. The result of implementing this method may  be helpful in cutting the cost of labour, saving the time spent to manually digitize the tree  counting method and improving the productivity of work.</abstract>
  <targetAudience authority="marctarget">specialized</targetAudience>
  <note type="statement of responsibility">Eiffel Syafhamka Nadimen A/l Syamsul</note>
  <note>Center for Mathematical Sciences</note>
  <note>Bachelor of Applied Science In Data Analytics With Honour -- Universiti Malaysia Pahang – 2023</note>
  <note>Includes bibliographical references</note>
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      <namePart>Center for Mathematical Sciences</namePart>
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    <topic>Universities and colleges</topic>
    <topic>Dissertations</topic>
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    <topic>Final Year Report</topic>
    <topic>Dissertations</topic>
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  <identifier type="isbn">THE0010045 (Local)</identifier>
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    <recordCreationDate encoding="marc">250509</recordCreationDate>
    <recordChangeDate encoding="iso8601">20251125111038.0</recordChangeDate>
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      <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
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