Deepak Gupta

According to our database, Deepak Gupta authored at least 62 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

EEG Signal Classification Using a Novel Universum-Based Twin Parametric-Margin Support Vector Machine.

Barenya Bikash Hazarika, Deepak Gupta, Bikram Kumar

Cogn. Comput., July, 2024

Application Layer Load Balancing in Software Defined Networking Using Priority Based Round Robin Scheduling Algorithm.

Neha Joshi, Deepak Gupta

Wirel. Pers. Commun., May, 2024

Deep feature extraction from EEG signals using xception model for emotion classification.

Arpan Phukan, Deepak Gupta

Multim. Tools Appl., March, 2024

Functional iterative approach for Universum-based primal twin bounded support vector machine to EEG classification (FUPTBSVM).

Deepak Gupta, Umesh Gupta, Hemanga Jyoti Sarma

Multim. Tools Appl., 2024

Fuzzy twin kernel ridge regression classifiers for liver disorder detection.

Deepak Gupta, Barenya Bikash Hazarika, Parashjyoti Borah

Int. J. Bus. Intell. Data Min., 2024

Wavelet kernel large margin distribution machine-based regression for modelling the river suspended sediment load.

Deepak Gupta, Barenya Bikash Hazarika, Mohanadhas Berlin

Comput. Electr. Eng., 2024

An efficient angle-based twin random vector functional link classifier.

Upendra Mishra, Deepak Gupta, Barenya Bikash Hazarika

Appl. Soft Comput., 2024

2023

Fuzzy twin support vector machine based on affinity and class probability for class imbalance learning.

Barenya Bikash Hazarika, Deepak Gupta, Parashjyoti Borah

Knowl. Inf. Syst., December, 2023

Mode decomposition based large margin distribution machines for sediment load prediction.

Barenya Bikash Hazarika, Deepak Gupta

Expert Syst. Appl., December, 2023

1-Norm twin random vector functional link networks based on Universum data for leaf disease detection.

Chittabarni Sarkar, Deepak Gupta, Barenya Bikash Hazarika

Appl. Soft Comput., November, 2023

Robust support vector quantile regression with truncated pinball loss (RSVQR).

Barenya Bikash Hazarika, Deepak Gupta, Parashjyoti Borah

Comput. Appl. Math., September, 2023

Leaf disease detection using machine learning and deep learning: Review and challenges.

Chittabarni Sarkar, Deepak Gupta, Umesh Gupta, Barenya Bikash Hazarika

Appl. Soft Comput., September, 2023

Least squares structural twin bounded support vector machine on class scatter.

Umesh Gupta, Deepak Gupta

Appl. Intell., June, 2023

Streamflow prediction in mountainous region using new machine learning and data preprocessing methods: a case study.

Rana Muhammad Adnan, Barenya Bikash Hazarika, Deepak Gupta, Salim Heddam, Özgür Kisi

Neural Comput. Appl., April, 2023

Improved twin bounded large margin distribution machines for binary classification.

Barenya Bikash Hazarika, Deepak Gupta

Multim. Tools Appl., April, 2023

An Intuitionistic Fuzzy Random Vector Functional Link Classifier.

Upendra Mishra, Deepak Gupta, Barenya Bikash Hazarika

Neural Process. Lett., 2023

2022

Density Weighted Twin Support Vector Machines for Binary Class Imbalance Learning.

Barenya Bikash Hazarika, Deepak Gupta

Neural Process. Lett., 2022

Data-driven mechanism based on fuzzy Lagrangian twin parametric-margin support vector machine for biomedical data analysis.

Deepak Gupta, Parashjyoti Borah, Usha Mary Sharma, Mukesh Prasad

Neural Comput. Appl., 2022

Bipolar fuzzy based least squares twin bounded support vector machine.

Umesh Gupta, Deepak Gupta

Fuzzy Sets Syst., 2022

Affinity and transformed class probability-based fuzzy least squares support vector machines.

Parashjyoti Borah, Deepak Gupta

Fuzzy Sets Syst., 2022

Random vector functional link with ε-insensitive Huber loss function for biomedical data classification.

Barenya Bikash Hazarika, Deepak Gupta

Comput. Methods Programs Biomed., 2022

2021

On Regularization Based Twin Support Vector Regression with Huber Loss.

Umesh Gupta, Deepak Gupta

Neural Process. Lett., 2021

Density-weighted support vector machines for binary class imbalance learning.

Barenya Bikash Hazarika, Deepak Gupta

Neural Comput. Appl., 2021

Computational approach to clinical diagnosis of diabetes disease: a comparative study.

Deepak Gupta, Ambika Choudhury, Umesh Gupta, Priyanka Singh, Mukesh Prasad

Multim. Tools Appl., 2021

Applying over 100 classifiers for churn prediction in telecom companies.

Debjyoti Das Adhikary, Deepak Gupta

Multim. Tools Appl., 2021

Regularized based implicit Lagrangian twin extreme learning machine in primal for pattern classification.

Umesh Gupta, Deepak Gupta

Int. J. Mach. Learn. Cybern., 2021

Kernel-Target Alignment Based Fuzzy Lagrangian Twin Bounded Support Vector Machine.

Umesh Gupta, Deepak Gupta

Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2021

Universum based Lagrangian twin bounded support vector machine to classify EEG signals.

Bikram Kumar, Deepak Gupta

Comput. Methods Programs Biomed., 2021

An intuitionistic fuzzy kernel ridge regression classifier for binary classification.

Barenya Bikash Hazarika, Deepak Gupta, Parashjyoti Borah

Appl. Soft Comput., 2021

On robust asymmetric Lagrangian ν-twin support vector regression using pinball loss function.

Deepak Gupta, Umesh Gupta

Appl. Soft Comput., 2021

Least squares large margin distribution machine for regression.

Umesh Gupta, Deepak Gupta

Appl. Intell., 2021

Robust twin bounded support vector machines for outliers and imbalanced data.

Parashjyoti Borah, Deepak Gupta

Appl. Intell., 2021

Efficient implicit Lagrangian twin parametric insensitive support vector regression via unconstrained minimization problems.

Deepak Gupta, Bharat Richhariya

Ann. Math. Artif. Intell., 2021

Multilevel Color Image Segmentation using Modified Fuzzy Entropy and Cuckoo Search Algorithm.

Shreya Pare, Mukesh Prasad, Deepak Puthal, Deepak Gupta, Anand Malik, Amit Saxena

Proceedings of the 30th IEEE International Conference on Fuzzy Systems, 2021

2020

Robust regularized extreme learning machine with asymmetric Huber loss function.

Deepak Gupta, Barenya Bikash Hazarika, Mohanadhas Berlin

Neural Comput. Appl., 2020

Lagrangian twin parametric insensitive support vector regression (LTPISVR).

Deepak Gupta, Kamalini Acharjee, Bharat Richhariya

Neural Comput. Appl., 2020

Functional iterative approaches for solving support vector classification problems based on generalized Huber loss.

Parashjyoti Borah, Deepak Gupta

Neural Comput. Appl., 2020

Modelling and forecasting of COVID-19 spread using wavelet-coupled random vector functional link networks.

Barenya Bikash Hazarika, Deepak Gupta

Appl. Soft Comput., 2020

Unconstrained convex minimization based implicit Lagrangian twin extreme learning machine for classification (ULTELMC).

Parashjyoti Borah, Deepak Gupta

Appl. Intell., 2020

A Two-Phase Approach for Semi-Supervised Feature Selection.

Amit Saxena, Shreya Pare, Mahendra Singh Meena, Deepak Gupta, Akshansh Gupta, Imran Razzak, Chin-Teng Lin, Mukesh Prasad

Algorithms, 2020

End-to-End Analysis for Text Detection and Recognition in Natural Scene Images.

Ahlam Alnefaie, Deepak Gupta, Monowar H. Bhuyan, Imran Razzak, Prashant Gupta, Mukesh Prasad

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

2019

A fuzzy twin support vector machine based on information entropy for class imbalance learning.

Deepak Gupta, Bharat Richhariya, Parashjyoti Borah

Neural Comput. Appl., 2019

Facial expression recognition using iterative universum twin support vector machine.

Bharat Richhariya, Deepak Gupta

Appl. Soft Comput., 2019

Unconstrained convex minimization based implicit Lagrangian twin random vector Functional-link networks for binary classification (ULTRVFLC).

Parashjyoti Borah, Deepak Gupta

Appl. Soft Comput., 2019

An improved regularization based Lagrangian asymmetric ν-twin support vector regression using pinball loss function.

Umesh Gupta, Deepak Gupta

Appl. Intell., 2019

Regularized Universum twin support vector machine for classification of EEG Signal.

Deepak Gupta, Hemanga Jyoti Sarma, Kshitij Mishra, Mukesh Prasad

Proceedings of the 2019 IEEE International Conference on Systems, Man and Cybernetics, 2019

2018

Entropy based fuzzy least squares twin support vector machine for class imbalance learning.

Deepak Gupta, Bharat Richhariya

Appl. Intell., 2018

Fusion based En-FEC Transfer Learning Approach for Automobile Parts Recognition System.

Mukesh Prasad, Shantanu Rajora, Deepak Gupta, Yousef-Awwad Daraghmi, Eman Yasser Daraghmi, Pranay Yadav, Prayag Tiwari, Amit Saxena

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2018

Kernel Target Alignment based Fuzzy Least Square Twin Bounded Support Vector Machine.

Umesh Gupta, Deepak Gupta, Mukesh Prasad

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2018

Improved 2-norm Based Fuzzy Least Squares Twin Support Vector Machine.

Parashjyoti Borah, Deepak Gupta, Mukesh Prasad

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2018

Online video streaming for human tracking based on weighted resampling particle filter.

Mukesh Prasad, Liang-Cheng Chang, Deepak Gupta, Mahardhika Pratama, Suresh Sundaram, Chin-Teng Lin

Proceedings of the INNS Conference on Big Data and Deep Learning 2018, 2018

2017

Training primal K-nearest neighbor based weighted twin support vector regression via unconstrained convex minimization.

Deepak Gupta

Appl. Intell., 2017

A new approach for training Lagrangian twin support vector machine via unconstrained convex minimization.

S. Balasundaram, Deepak Gupta, Subhash Chandra Prasad

Appl. Intell., 2017

A fuzzy based Lagrangian twin parametric-margin support vector machine (FLTPMSVM).

Deepak Gupta, Parashjyoti Borah, Mukesh Prasad

Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

Block-based feature extraction model for early fire detection.

Kuang-Pen Chou, Mukesh Prasad, Deepak Gupta, Sharmi Sankar, Ting-Wei Xu, Suresh Sundaram, Chin-Teng Lin, Wen-Chieh Lin

Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

2016

Knowledge-based extreme learning machines.

S. Balasundaram, Deepak Gupta

Neural Comput. Appl., 2016

On optimization based extreme learning machine in primal for regression and classification by functional iterative method.

S. Balasundaram, Deepak Gupta

Int. J. Mach. Learn. Cybern., 2016

2014

Lagrangian support vector regression via unconstrained convex minimization.

S. Balasundaram, Deepak Gupta, Kapil

Neural Networks, 2014

Training Lagrangian twin support vector regression via unconstrained convex minimization.

S. Balasundaram, Deepak Gupta

Knowl. Based Syst., 2014

1-Norm extreme learning machine for regression and multiclass classification using Newton method.

S. Balasundaram, Deepak Gupta, Kapil

Neurocomputing, 2014

On implicit Lagrangian twin support vector regression by Newton method.

S. Balasundaram, Deepak Gupta

Int. J. Comput. Intell. Syst., 2014

2013

A Heuristic for Permutation Flowshop Scheduling to Minimize Makespan.

Deepak Gupta, Kewal Krishan Nailwal, Sameer Sharma

Proceedings of the Third International Conference on Soft Computing for Problem Solving, 2013