Deep Learning based Pathogen Infestation Detection In Plants
| Autor: | S. Mohana Priya, D. Pushgara Rani, J. Ranjani, S.M. Vignesh Kumar, V.K.G. Kalaiselvi |
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| Rok vydání: | 2021 |
| Předmět: |
Computer science
Agroforestry Fauna Outbreak Climate change 020207 software engineering 04 agricultural and veterinary sciences 02 engineering and technology Subtropics Virus diseases Pesticide medicine.disease_cause Infestation 040103 agronomy & agriculture 0202 electrical engineering electronic engineering information engineering medicine 0401 agriculture forestry and fisheries Arable land |
| Zdroj: | 2021 5th International Conference on Intelligent Computing and Control Systems (ICICCS). |
| Popis: | India boasts forest and tree cover comprising 24.56% of its total geographical area and an arable land area of 159.7 million hectares. This inevitably calls for the need for fauna management. Tropical and subtropical climates are ideal for the growth and development of pathogens and pests. Although India is a proud home to a huge variety of crops, plants, trees, it also finds virus diseases and their vectors in abundance. Continual usage of antifungal agents, insecticides, and pesticides is increasing the immunogenicity of pathogens. The rapid fluctuations in climate change are also playing a role in increasing disease rates exponentially. Misdiagnosis of disease impacting crops could lead to misuse of chemicals and emergence of resistant pathogen strains, an outbreak of new plant diseases, economic loss, environmental impacts, and increased input costs. Manual inspection and diagnosis are expensive and time inefficient. The application is a deep-learning powered computer vision-aided application that is rendered in a cross platform mobile application that takes charge by examining the disease rate of leaves and provides trend pattern with insightful analysis and accuracy checkpoints towards nurturing better lives for plants. |
| Databáze: | OpenAIRE |
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