A survey on plant disease prediction using machine learning and deep learning techniques

A survey on plant disease prediction using machine learning and deep learning techniques

The major agricultural products in India are rice, wheat, pulses, and spices. As our population is increasing rapidly the demand for agriculture products also increasing alarmingly. A huge amount of data are incremented from various field of agriculture. Analysis of this data helps in predicting the...

Full description

Bibliographic Details
Main Authors:	UshaDevi G, gokulnath BV
Format:	Article
Language:	English
Published:	Asociación Española para la Inteligencia Artificial 2020-07-01
Series:	Inteligencia Artificial
Subjects:	Plant disease prediction, Crop productivity, Support vector machine, Deep learning, Meteorological factor, Visual symptoms, Random forest
Online Access:	https://journal.iberamia.org/index.php/intartif/article/view/474

Similar Items

Machine Learning and Conventional Methods for Reference Evapotranspiration Estimation Using Limited-Climatic-Data Scenarios
by: Pietros André Balbino dos Santos, et al.
Published: (2023-09-01)

Designing a European-Wide Crop Type Mapping Approach Based on Machine Learning Algorithms Using LUCAS Field Survey and Sentinel-2 Data
by: Babak Ghassemi, et al.
Published: (2022-01-01)

MACHINE LEARNING TECHNIQUES FOR EARLY HEART FAILURE PREDICTION
by: Nur Shahellin Mansur Huang, et al.
Published: (2021-08-01)

Machine learning technique in the north zagros earthquake prediction
by: Salma Ommi, et al.
Published: (2024-06-01)

A Comparative Study of Machine Learning Techniques for Wind Turbine Performance Prediction
by: Muralidharan S., et al.
Published: (2023-01-01)

Detection of developmental dyslexia with machine learning using eye movement data
by: Peter Raatikainen, et al.
Published: (2021-12-01)

Integrated Deep Learning and Supervised Machine Learning Model for Predictive Fetal Monitoring
by: Vinayaka Gude, et al.
Published: (2022-11-01)

Performance of Machine Learning Techniques for Meteorological Drought Forecasting in the Wadi Mina Basin, Algeria
by: Mohammed Achite, et al.
Published: (2023-02-01)

Prediction Models for Obstructive Sleep Apnea in Korean Adults Using Machine Learning Techniques
by: Young Jae Kim, et al.
Published: (2021-03-01)

Classification of WatSan Technologies Using Machine Learning Techniques
by: Hala Al Nuaimi, et al.
Published: (2023-08-01)

A Machine Learning Approach for Rainfall Nowcasting Using Numerical Model and Observational Data
by: Georgios Kyros, et al.
Published: (2023-08-01)

Real time photovoltaic power forecasting and modelling using machine learning techniques
by: Mwende Rita, et al.
Published: (2022-01-01)

Estimation of Spring Maize Evapotranspiration in Semi-Arid Regions of Northeast China Using Machine Learning: An Improved SVR Model Based on PSO and RF Algorithms
by: Wenjie Hou, et al.
Published: (2023-04-01)

Predicting Bitcoin Prices Using Machine Learning
by: Athanasia Dimitriadou, et al.
Published: (2023-05-01)

Pre-Constrained Machine Learning Method for Multi-Year Mapping of Three Major Crops in a Large Irrigation District
by: Yeqiang Wen, et al.
Published: (2019-01-01)

Diabetes Classification Using Machine Learning Techniques
by: Methaporn Phongying, et al.
Published: (2023-05-01)

Machine learning based diabetes prediction and development of smart web application
by: Nazin Ahmed, et al.
Published: (2021-06-01)

Harnessing Machine Learning Techniques for Mapping Aquaculture Waterbodies in Bangladesh
by: Hannah Ferriby, et al.
Published: (2021-12-01)

Forecasting Wind Energy Production Using Machine Learning Techniques
by: Margarat G. Simi, et al.
Published: (2023-01-01)

hERG-toxicity prediction using traditional machine learning and advanced deep learning techniques
by: Erik Ylipää, et al.
Published: (2023-01-01)

Machine Learning Techniques for Gully Erosion Susceptibility Mapping: A Review
by: Hamid Mohebzadeh, et al.
Published: (2022-11-01)

Analysis of geo-spatiotemporal data using machine learning algorithms and reliability enhancement for urbanization decision support
by: Kwame O. Hackman, et al.
Published: (2020-12-01)

Data Driven Prognosis of Cervical Cancer Using Class Balancing and Machine Learning Techniques
by: Mamta Arora, et al.
Published: (2020-11-01)

Credit card attrition: an overview of machine learning and deep learning techniques
by: Сихао Ван, et al.
Published: (2023-11-01)

Predicting benzodiazepine prescriptions: A proof-of-concept machine learning approach
by: Kerry L. Kinney, et al.
Published: (2023-03-01)

Machine Learning-Based Epileptic Seizure Detection Methods Using Wavelet and EMD-Based Decomposition Techniques: A Review
by: Rabindra Gandhi Thangarajoo, et al.
Published: (2021-12-01)

The Application of the Machine Learning Method in Electromyographic Data
by: Tao Liu, et al.
Published: (2020-01-01)

Identification of Weather Influences on Flight Punctuality Using Machine Learning Approach
by: Sakdirat Kaewunruen, et al.
Published: (2021-08-01)

The optimal crowd learning machine
by: Bilguunzaya Battogtokh, et al.
Published: (2017-05-01)

Chronic kidney disease prediction using machine learning techniques
by: Dibaba Adeba Debal, et al.
Published: (2022-11-01)

Prediction of the Compressive Strength of Vibrocentrifuged Concrete Using Machine Learning Methods
by: Alexey N. Beskopylny, et al.
Published: (2024-02-01)

Machine Learning Algorithms Performance Evaluation for Intrusion Detection
by: Shyla ., et al.
Published: (2021-01-01)

Lightweight approach for malicious domain detection using machine learning
by: Ganesan Pradeepa, et al.
Published: (2022-04-01)

Prediction of the Area of High-Turbidity Water in the Yatsushiro Sea, Japan, Using Machine Learning with Satellite, Meteorological, and Oceanographic Data
by: Kazutaka Nagayama, et al.
Published: (2023-03-01)

Computation of High-Performance Concrete Compressive Strength Using Standalone and Ensembled Machine Learning Techniques
by: Yue Xu, et al.
Published: (2021-11-01)

Comparison of machine learning and deep learning techniques in promoter prediction across diverse species
by: Nikita Bhandari, et al.
Published: (2021-02-01)

Application of Machine Learning in Fuel Cell Research
by: Danqi Su, et al.
Published: (2023-05-01)

A novel approach to predict competency and the hidden risk factor by using various machine learning classifiers
by: Stalin M., et al.
Published: (2023-07-01)

Compressive Strength Prediction of Fly Ash Concrete Using Machine Learning Techniques
by: Yimin Jiang, et al.
Published: (2022-05-01)

Landslide susceptibility prediction and identification of its main environmental factors based on machine learning models
by: Faming Huang, et al.
Published: (2022-03-01)