Pest Detection in Crops Using Deep Neural Networks

Jayanthi, B.; Priyanka, T. Anu; Shalini, V. Baby; Grace, R. Kingsy

doi:10.1109/icaccs54159.2022.9785155

Cited by 5 publications

(1 citation statement)

References 12 publications

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“…Look into the predicted plant illness at the wrong time, (Jayanthi, Priyanka, Shalini, & Grace, 2022). New methods for identifying and detecting insect pests have been developed despite the drawbacks of the conventional convolution neural network (CNN)based approach.…”

Section: Figure 3: Study Identification Prisma Flowchartmentioning

confidence: 99%

Artificial Intelligence Techniques for the Pest Detection in Banana Field: A Systematic Review

Nasim,

Rashid,

Syed

et al. 2023

Pak. J. Biotechnol

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Purpose: This systematic review details the diseases that influence banana production and their detection. A common method for identifying plant diseases in plants is image processing. Segmentation is one method for using image processing to establish medical diagnosis. The main objective of this study is to identify, categorize, and evaluate several image processing techniques used to control pests in a banana crop. Methodology: An electronic search was conducted using relevant keywords on openly available databases including IEEE Xplore, PubMed, Science Direct, and Google Scholar. 104 items were discovered by the search engine. After removing the duplicates, there were 56 research papers remained, but 22 of them were discarded after title and abstract checks since they did not address insect detection in banana fields. Results: 22 papers that come under the headings of image classification, AI/ML, deep learning, and mobile applications provide usable and reliable detection techniques in this systematic review

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Section: Figure 3: Study Identification Prisma Flowchartmentioning

confidence: 99%