Plant Disease Detection through External Camera Sensors using Deep Learning Techniques
Agriculture is one of the most important aspect of a country for its economy and livelihood. A country is dependent on its farmers for livelihood and for providing raw material for food. Therefore, crop yield is extremely essential. One of things that interfere with good crop yield is diseases in plants. Diseases in plants can occur due to variety of factors like temperature, fertility of soil, type of soil, pH of the soil and moisture of the soil. Quick and accurate detection is extremely necessary for eradication of plant diseases. Traditionally, disease of the plant is identified by visually studying the leaf by the naked eye. But this process takes considerable time of the farmer and may not be the efficient method for identifying diseases. Image Processing techniques, along with a classification algorithm solves this problem by observing patterns on plant leaves. We aim to build a solution which is able to capture image through external camera sources like mobile camera, webcam and extract features with image processing techniques and classify disease with Deep Neural Network Algorithm.
Authors
- Dipak Ghosh (ORCID: https://orcid.org/0000-0003-3768-8091)
- Prabhat Kumar Srivastava (ORCID: https://orcid.org/0000-0002-9467-6719)
- Uttkarsh Thakur
- Amit Arora (ORCID: https://orcid.org/0009-0001-8841-0316)
Institutions
- Galgotias University (IN)
Publication Details
- Published
- 2024-08-29
- DOI
- https://doi.org/10.1109/iceect61758.2024.10739028
- Citations
- 1
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 0.60