A Deep Learning Approach for Detection of Disease and Classification of Fruits
The calorie component of fruit is identified using a common photo dataset and several machine learning advancements, including Pre-processing, segmentation, function extraction, and classification which is primarily based on size and shape. Using image processing methods, the dimensions of fruit objects are calculated. Finally, we'll provide users and patients with the best advice for fruit consumption based on our best estimates of the number of calories in the fruit. To help farmers save time and money while improving the accuracy of plant disease detection, we have developed a technology. Thanks to the usage of many speed-enhancing methods, it outperforms competing systems. An easy-to- implement method for picture segmentation, classification, and reconstruction, the SVM Algorithm is what we're employing here. Even when the objective function isn't acting well, it may nevertheless perform well during global optimization.
Authors
- M. Sree Sushmita
- Sharanabasappa Madival
Publication Details
- Journal
- International Journal of Innovative Science and Research Technology (IJISRT)
- Published
- 2024-08-20
- DOI
- https://doi.org/10.38124/ijisrt/ijisrt24aug177
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00