9 Ocak 2023 Konferans bildirisi Açık Erişim

Güzel Mustafa; Turan Bülent; Şin Bahadır; Baştürk Alper

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        "affiliation": "Tokat Gaziosmanpa\u015fa \u00dcniversitesi", 
        "name": "G\u00fczel Mustafa"
      }, 
      {
        "affiliation": "Tokat Gaziosmanpa\u015fa \u00dcniversitesi", 
        "name": "Turan B\u00fclent"
      }, 
      {
        "affiliation": "Sakarya Uygulamal\u0131 Bilimler \u00dcniversitesi", 
        "name": "\u015ein Bahad\u0131r"
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        "affiliation": "Erciyes \u00dcniversitesi", 
        "name": "Ba\u015ft\u00fcrk Alper"
      }
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    "description": "<p>The knowledge of weed numbers is very helpful for many studies due to minimizing weed harm<br>\non the crops as well as knowing the weed species and classes. In this study, we used a deep learning<br>\narchitecture that was capable of detecting some weeds to count the weed numbers instead of classical<br>\nmanual weed counting methods. The pre-trained deep learning weight belongs to YOLOv5 which<br>\nis used in this study, can detect 5 different phenological terms (cotyledon leaves period, 3-5 leaves<br>\nperiod, pre-flowering period, flowering period, and fruit and seed setting period) of some harmful weeds<br>\n(sherlock mustard-Sinapis arvensis L., creeping thistle-Cirsium arvense L. Scop, and forking larkspur-<br>\nConsolida regalis Gray) in wheat production and other crops with 98% highest accuracy. StrongSORT<br>\nwith the OSNet tool is used as the multi-object tracker. The weeds successfully counted from any image<br>\nresources (image, video, webcam, etc.) while avoiding recounting the same object by computer vision. It<br>\nplays an important role in the studies aimed to understand weeds population spread, resistance gaining to<br>\nherbicides by weeds, the economical threshold of weeds, etc. It also provides these parameters cheaper<br>\nand faster than classical methods.</p>", 
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    "keywords": [
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      "deep learning", 
      "StrongSORT"
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    "publication_date": "2023-01-09", 
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    "science_branches": [
      "Teknik Bilimler > Bilgisayar Bilimleri > Bilgisayarla G\u00f6rme"
    ], 
    "title": "COUNTING OF WEED NUMBERS IN FARMS BY DEEP LEARNING-STRONGSORT", 
    "tubitak_grants": [
      {
        "program": "3501", 
        "project_number": "120O888", 
        "workgroup": "TOVAG"
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