Ravinesh C. Deo

According to our database1, Ravinesh C. Deo authored at least 30 papers between 2015 and 2022.

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PhD thesis 


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On csauthors.net:


Kernel Ridge Regression Hybrid Method for Wheat Yield Prediction with Satellite-Derived Predictors.
Remote. Sens., 2022

Hybrid deep CNN-SVR algorithm for solar radiation prediction problems in Queensland, Australia.
Eng. Appl. Artif. Intell., 2022

Cloud Affected Solar UV Prediction With Three-Phase Wavelet Hybrid Convolutional Long Short-Term Memory Network Multi-Step Forecast System.
IEEE Access, 2022

Student Performance Predictions for Advanced Engineering Mathematics Course With New Multivariate Copula Models.
IEEE Access, 2022

Application of Deep Learning Models for Automated Identification of Parkinson's Disease: A Review (2011-2021).
Sensors, 2021

Deep Learning Forecasts of Soil Moisture: Convolutional Neural Network and Gated Recurrent Unit Models Coupled with Satellite-Derived MODIS, Observations and Synoptic-Scale Climate Index Data.
Remote. Sens., 2021

An Eigenvalues-Based Covariance Matrix Bootstrap Model Integrated With Support Vector Machines for Multichannel EEG Signals Analysis.
Frontiers Neuroinformatics, 2021

Modeling soil temperature using air temperature features in diverse climatic conditions with complementary machine learning models.
Comput. Electron. Agric., 2021

A new framework for classification of multi-category hand grasps using EMG signals.
Artif. Intell. Medicine, 2021

Designing Deep-Based Learning Flood Forecast Model With ConvLSTM Hybrid Algorithm.
IEEE Access, 2021

Deep Multi-Stage Reference Evapotranspiration Forecasting Model: Multivariate Empirical Mode Decomposition Integrated With the Boruta-Random Forest Algorithm.
IEEE Access, 2021

Development and evaluation of the cascade correlation neural network and the random forest models for river stage and river flow prediction in Australia.
Soft Comput., 2020

A general extensible learning approach for multi-disease recommendations in a telehealth environment.
Pattern Recognit. Lett., 2020

An ensemble tree-based machine learning model for predicting the uniaxial compressive strength of travertine rocks.
Neural Comput. Appl., 2020

Enhanced deep learning algorithm development to detect pain intensity from facial expression images.
Expert Syst. Appl., 2020

Adaptive boost LS-SVM classification approach for time-series signal classification in epileptic seizure diagnosis applications.
Expert Syst. Appl., 2020

The modeling of human facial pain intensity based on Temporal Convolutional Networks trained with video frames in HSV color space.
Appl. Soft Comput., 2020

Ensemble neural network approach detecting pain intensity from facial expressions.
Artif. Intell. Medicine, 2020

Deep Air Quality Forecasts: Suspended Particulate Matter Modeling With Convolutional Neural and Long Short-Term Memory Networks.
IEEE Access, 2020

Global Solar Radiation Estimation and Climatic Variability Analysis Using Extreme Learning Machine Based Predictive Model.
IEEE Access, 2020

Modern Artificial Intelligence Model Development for Undergraduate Student Performance Prediction: An Investigation on Engineering Mathematics Courses.
IEEE Access, 2020

Sleep EEG signal analysis based on correlation graph similarity coupled with an ensemble extreme machine learning algorithm.
Expert Syst. Appl., 2019

Fractal dimension undirected correlation graph-based support vector machine model for identification of focal and non-focal electroencephalography signals.
Biomed. Signal Process. Control., 2019

A Joint Deep Neural Network Model for Pain Recognition from Face.
Proceedings of the IEEE 4th International Conference on Computer and Communication Systems, 2019

Survey of different data-intelligent modeling strategies for forecasting air temperature using geographic information as model predictors.
Comput. Electron. Agric., 2018

Artificial intelligence approach for the prediction of Robusta coffee yield using soil fertility properties.
Comput. Electron. Agric., 2018

Multi-stage committee based extreme learning machine model incorporating the influence of climate parameters and seasonality on drought forecasting.
Comput. Electron. Agric., 2018

Predicting compressive strength of lightweight foamed concrete using extreme learning machine model.
Adv. Eng. Softw., 2018

Short-term electricity demand forecasting with MARS, SVR and ARIMA models using aggregated demand data in Queensland, Australia.
Adv. Eng. Informatics, 2018

Prediction of SPEI Using MLR and ANN: A Case Study for Wilsons Promontory Station in Victoria.
Proceedings of the 14th IEEE International Conference on Machine Learning and Applications, 2015