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A Comprehensive Review on Automatic Detection and Early Prediction of Tomato Diseases and Pests Control Based on Leaf/Fruit Images

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International Conference on Cyber Security, Privacy and Networking (ICSPN 2022) (ICSPN 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 599))

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Abstract

Recently, deep learning has proven to be extremely effective in solving challenges connected to the identification of plant diseases. Nevertheless, when a model trained on a specific dataset is assessed in new greenhouse settings, poor performance is seen. Because of this, we provide a way to increase model accuracy by utilizing strategies that can enable the model’s generalization capabilities be refined to deal with complicated changes in new greenhouse conditions in this paper. In order to build and test a deep learning-based detector, we utilize photos from greenhouses to train and test the detector. To test the system’s inference on new greenhouse data, we utilize the characteristics developed in the previous step to identify target classes. So, our model can differentiate data changes that strengthen the system when applied to new situations by having precise control over inter- and intra-class variations. Using the different inference dataset, we review the different target classes with different type of methodology. The researchers in our field of plant disease recognition feel that our study provides useful suggestions for their future work.

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Author information

Authors and Affiliations

  1. JECRC University, Jaipur, India

    Saurabh Sharma, Gajanand Sharma & Ekta Menghani

  2. Aryabhatta College of Engineering & Research Center, Ajmer, India

    Anupama Sharma

Authors
  1. Saurabh Sharma
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  2. Gajanand Sharma
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  3. Ekta Menghani
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  4. Anupama Sharma
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Corresponding author

Correspondence to Saurabh Sharma .

Editor information

Editors and Affiliations

  1. Electronics Engineering and Telecom, State University of Rio de Janeiro, Rio de Janeiro, Brazil

    Nadia Nedjah

  2. University of Murcia, Murcia, Spain

    Gregorio Martínez Pérez

  3. Asia University, Taichung, Taiwan

    B. B. Gupta

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Sharma, S., Sharma, G., Menghani, E., Sharma, A. (2023). A Comprehensive Review on Automatic Detection and Early Prediction of Tomato Diseases and Pests Control Based on Leaf/Fruit Images. In: Nedjah, N., Martínez Pérez, G., Gupta, B.B. (eds) International Conference on Cyber Security, Privacy and Networking (ICSPN 2022). ICSPN 2021. Lecture Notes in Networks and Systems, vol 599. Springer, Cham. https://doi.org/10.1007/978-3-031-22018-0_26

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