DenseNet-201 and Xception Pre-Trained Deep Learning Models for Fruit Recognition

Farsana Salim, Faisal Saeed*, Shadi Basurra, Sultan Noman Qasem, Tawfik Al-Hadhrami

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    16 Citations (SciVal)
    Original languageEnglish
    Article number3132
    JournalElectronics (Switzerland)
    Volume12
    Issue number14
    DOIs
    Publication statusPublished (VoR) - Jul 2023

    Funding

    The authors extend their appreciation to the Deanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University (IMSIU) for funding and supporting this work through Research Partnership Program no. RP-21-07-09.

    FundersFunder number
    Al-Imam Muhammad Ibn Saud Islamic UniversityRP-21-07-09
    Deanship of Scientific Research, Imam Mohammed Ibn Saud Islamic University

      Keywords

      • DenseNet
      • food security
      • fruit recognition
      • MobileNetV3
      • pre-trained models
      • ResNet
      • Xception

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