| Autor: |
Gomathy, B., Nirmala, V., Ramesh, S. M. |
| Předmět: |
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| Zdroj: |
AIP Conference Proceedings; 2023, Vol. 2764 Issue 1, p1-12, 12p |
| Abstrakt: |
In Indian agriculture, the monitoring of the productivity rate of each and every Vegetables/Millets takes an important task. The leaves and stems of the plants are affected by the various diseases such as mildew, anthracnose, leaf-spot, etc. Hence, we are in need to monitor the plants effectively to improve the productivity rate of the Indian agricultural products. So, this paper mainly focused on the pumpkin leaf analysis and detection of the diseases those are presented in the pumpkin leaf images. The entire detection process is held with the help of the Image processing algorithms such as fuzzy based pre-processing, Neural Network based classification and CV based feature extraction. The paper presents the detailed study and analysis of all these three stages. In classifier stage, the feed forward neural network of sizes 10, 8 and 5 have implemented to categorize the affected images from the pumpkin leaf dataset. The parameter cross-entropy is mainly employed for validating the classifier performance. The investigational results illustrate that the proposed classifier efficiently works with minimum amount of cross-entropy rate. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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