.

ISSN 2063-5346
For urgent queries please contact : +918130348310

ESTIMATE ACCURACY IN IMAGE PLANT DISEASES DETECTION USING CONVOLUTIONAL NEURAL NETWORK COMPARED WITH PULSECOUPLED NEURAL NETWORK

Main Article Content

Veeravelli Ganesh, A. Gayathri
» doi: 10.31838/ecb/2023.12.sa1.399

Abstract

Aim: The main aim of the research work is to estimate accuracy in Image plant disease detection using Convolutional Neural Network over Pulse-Coupled Neural Network. Materials and Methods: Convolutional Neural Network and Pulsed-Coupled Neural Network are implemented in this research work. Sample size is calculated using G power software and determined as 10 per group with pretest power 80%. Results and Discussion: Convolutional Neural Network provides a higher of 88.21% compared to Pulse- Coupled Neural Network with 83.95% in predicting plant disease in plant diseases detection. There are statistically significant differences between study groups with p = 0.045 (p<0.05) Independent T-test value states that the results in the study are insignificant. Conclusion: Convolutional Neural Network gives better accuracy then Pulse-Coupled Neural Network.

Article Details