In the field of artificial intelligence, deep learning is a sub-field. Automatic learning and feature extraction have piqued the interest of academics and industry alike in recent years. It is widely used in voice, natural language, image and video processing. At the same time, it has evolved as a hub for research in the area of agricultural plant protection, including, among other things, the assessment of plant disease detection. It is possible to avoid the drawbacks of artificially selecting disease spot features by using deep learning in plant disease identification, as well as to increase the objectivity of extracting plant disease feature data and the pace of technological transformation. Deep learning technology has made significant progress in the crop disease detection field in recent years. Plant leaf disease recognition and classification using deep learning and advanced imaging techniques review is the focus of this paper. This research study will be useful to those who investigate the plant diseases. Some of the present challenges and issues were also analyzed.


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    Titel :

    Review on deep learning-based plant disease detection


    Beteiligte:
    Bhise, Dhiraj (Autor:in) / Kumar, Sunil (Autor:in) / Mohapatra, Hitesh (Autor:in)


    Erscheinungsdatum :

    01.12.2022


    Format / Umfang :

    375322 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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