Classification and Prediction of Rice Crop Diseases Using CNN and PNN

Author:

Limkar Suresh,Kulkarni Sneha,Chinchmalatpure Prajwal,Sharma Divya,Desai Mithila,Angadi Shivani,Jadhav Pushkar

Publisher

Springer Singapore

Reference25 articles.

1. Rehman, A., Jingdong, L., Khatoon, R., Hussain, M.I.: Modern agricultural technology adoption its importance, role and usage for the improvement of agriculture. Am. Eurasian J. Agric. Environ. Sci. 16, 284–288 (2016). https://doi.org/10.5829/idosi.aejaes.2016.16.2.12840

2. Gandhi, N., Armstrong, L.J., Petkar, O.: Predicting rice crop yield using Bayesian networks. In: 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Jaipur, pp. 795–799 (2016). https://doi.org/10.1109/icacci.2016.7732143

3. [Available online on 13-10-2019]. https://www.sgs.com/en/agriculture-food/seed-and-crop/crop-monitoring-and-agronomic-services/crop-monitoring

4. [Available on 13-10-2019]. https://mindbowser.com/solve-agricultural-problems-using-machine-learning

5. Yun, S., Xianfeng, W., et al.: PNN based crop disease recognition with leaf image features and meteorological data. 8(4) (2015)

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