Cite this DOI

Khened, A., Lokhande, H. N., & Gote, P. (2021). Touchless System for Fruits Sorting and Packaging in Shops. *Journal of Science & Technology*, *06*(01), 107–113. https://doi.org/10.46243/jst.2021.v6.i04.pp107-113

@article{khened2021touchless,
  author    = {Khened, Apoorva and Lokhande, Harshad N. and Gote, Pratiksha},
  title     = {{Touchless System for Fruits Sorting and Packaging in Shops}},
  journal   = {Journal of Science \& Technology},
  year      = {2021},
  month     = {aug},
  volume    = {06},
  number    = {01},
  pages     = {107--113},
  publisher = {Longman Publishers},
  issn      = {2456-5660},
  doi       = {10.46243/jst.2021.v6.i04.pp107-113},
  url       = {https://doi.org/10.46243/jst.2021.v6.i04.pp107-113},
  language  = {en},
  abstract  = {The time required to discover the product and ready with inside the lengthy queue for checkout of the shops is a common problem in our everyday lives. The automatic shop is the answer proposed to such problems. These shops are significant for each financial and social development because it reduces the efforts of guide operation and is time- saving. This system is a need of an hour these days since Covid-19 denies us to make direct contact with fruits or vegetables. Now-a-days deep learning gives evolution with brilliant performance in object detection. This paper gives solution as, robotics based totally automatic shop which uses deep learning to classify the products which helps to save our efforts and time. The Mobile-Net is used to detection of fruits on 2 classes with 85\% accuracy in detection. Robotics combined with virtual technology inclusive of picture detection, cloud and analytics, makes the structures correct and supplies more modern efficiencies.}
}

TY  - JOUR
TI  - Touchless System for Fruits Sorting and Packaging in Shops
AU  - Khened, Apoorva
AU  - Lokhande, Harshad N.
AU  - Gote, Pratiksha
JO  - Journal of Science & Technology
PY  - 2021
DA  - 2021/08/16/
VL  - 06
IS  - 01
SP  - 107
EP  - 113
PB  - Longman Publishers
SN  - 2456-5660
LA  - en
AB  - The time required to discover the product and ready with inside the lengthy queue for checkout of the shops is a common problem in our everyday lives. The automatic shop is the answer proposed to such problems. These shops are significant for each financial and social development because it reduces the efforts of guide operation and is time- saving. This system is a need of an hour these days since Covid-19 denies us to make direct contact with fruits or vegetables. Now-a-days deep learning gives evolution with brilliant performance in object detection. This paper gives solution as, robotics based totally automatic shop which uses deep learning to classify the products which helps to save our efforts and time. The Mobile-Net is used to detection of fruits on 2 classes with 85% accuracy in detection. Robotics combined with virtual technology inclusive of picture detection, cloud and analytics, makes the structures correct and supplies more modern efficiencies.
DO  - 10.46243/jst.2021.v6.i04.pp107-113
UR  - https://doi.org/10.46243/jst.2021.v6.i04.pp107-113
ER  -

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    "DOI": "10.46243/jst.2021.v6.i04.pp107-113",
    "URL": "https://doi.org/10.46243/jst.2021.v6.i04.pp107-113",
    "title": "Touchless System for Fruits Sorting and Packaging in Shops",
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    "container-title": "Journal of Science & Technology",
    "author": [
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    "publisher": "Longman Publishers",
    "language": "en",
    "abstract": "The time required to discover the product and ready with inside the lengthy queue for checkout of the shops is a common problem in our everyday lives. The automatic shop is the answer proposed to such problems. These shops are significant for each financial and social development because it reduces the efforts of guide operation and is time- saving. This system is a need of an hour these days since Covid-19 denies us to make direct contact with fruits or vegetables. Now-a-days deep learning gives evolution with brilliant performance in object detection. This paper gives solution as, robotics based totally automatic shop which uses deep learning to classify the products which helps to save our efforts and time. The Mobile-Net is used to detection of fruits on 2 classes with 85% accuracy in detection. Robotics combined with virtual technology inclusive of picture detection, cloud and analytics, makes the structures correct and supplies more modern efficiencies.",
    "ISSN": "2456-5660"
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From the record as registered (version 2) — the record and its history. Programs: https://registry.smartscholars.in/api.php?action=cite&doi=10.46243%2Fjst.2021.v6.i04.pp107-113 gives all four in one JSON answer.