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ORCIDDeepak Gupta 0004
Person information
- affiliation: National Institute of Technology Arunachal Pradesh, Department of Computer Science and Engineering, Yupia, India
Other persons with the same name
- Deepak Gupta — disambiguation page
- Deepak Gupta 0001 — Indian Institute of Technology, Kanpur, Department of Computer Science and Engineering, India
- Deepak Gupta 0002
![[0000-0002-3019-7161]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0002-3019-7161")
— GGSIP University, Maharaja Agrasen Institute of Technology, Delhi, India - Deepak Gupta 0003 — Amrita University, School of Business, Coimbatore, India
- Deepak Gupta 0005 — Thapar University, Department of Computer Science and Engineering, Patiala, India
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2020 – today
- 2024
[j48]Deepak Gupta, Barenya Bikash Hazarika, Parashjyoti Borah:
Fuzzy twin kernel ridge regression classifiers for liver disorder detection. Int. J. Bus. Intell. Data Min. 24(2): 131-145 (2024)- [j47]Deepak Gupta, Umesh Gupta, Hemanga Jyoti Sarma:
Functional iterative approach for Universum-based primal twin bounded support vector machine to EEG classification (FUPTBSVM). Multim. Tools Appl. 83(8): 22119-22151 (2024) - [j46]Arpan Phukan, Deepak Gupta:
Deep feature extraction from EEG signals using xception model for emotion classification. Multim. Tools Appl. 83(11): 33445-33463 (2024) - 2023
- [j45]Umesh Gupta, Deepak Gupta:
Least squares structural twin bounded support vector machine on class scatter. Appl. Intell. 53(12): 15321-15351 (2023) - [j44]Chittabarni Sarkar, Deepak Gupta, Umesh Gupta, Barenya Bikash Hazarika:
Leaf disease detection using machine learning and deep learning: Review and challenges. Appl. Soft Comput. 145: 110534 (2023) - [j43]Chittabarni Sarkar, Deepak Gupta, Barenya Bikash Hazarika:
1-Norm twin random vector functional link networks based on Universum data for leaf disease detection. Appl. Soft Comput. 148: 110850 (2023) - [j42]Barenya Bikash Hazarika, Deepak Gupta, Parashjyoti Borah:
Robust support vector quantile regression with truncated pinball loss (RSVQR). Comput. Appl. Math. 42(6): 283 (2023) - [j41]Barenya Bikash Hazarika, Deepak Gupta:
Mode decomposition based large margin distribution machines for sediment load prediction. Expert Syst. Appl. 232: 120844 (2023) - [j40]Barenya Bikash Hazarika, Deepak Gupta, Parashjyoti Borah:
Fuzzy twin support vector machine based on affinity and class probability for class imbalance learning. Knowl. Inf. Syst. 65(12): 5259-5288 (2023) - [j39]Barenya Bikash Hazarika, Deepak Gupta:
Improved twin bounded large margin distribution machines for binary classification. Multim. Tools Appl. 82(9): 13341-13368 (2023) - [j38]Rana Muhammad Adnan, Barenya Bikash Hazarika, Deepak Gupta, Salim Heddam, Özgür Kisi:
Streamflow prediction in mountainous region using new machine learning and data preprocessing methods: a case study. Neural Comput. Appl. 35(12): 9053-9070 (2023) - [j37]Upendra Mishra, Deepak Gupta, Barenya Bikash Hazarika:
An Intuitionistic Fuzzy Random Vector Functional Link Classifier. Neural Process. Lett. 55(4): 4325-4346 (2023) - 2022
- [j36]Barenya Bikash Hazarika, Deepak Gupta:
Random vector functional link with ε-insensitive Huber loss function for biomedical data classification. Comput. Methods Programs Biomed. 215: 106622 (2022) - [j35]Parashjyoti Borah, Deepak Gupta:
Affinity and transformed class probability-based fuzzy least squares support vector machines. Fuzzy Sets Syst. 443(Part): 203-235 (2022) - [j34]Umesh Gupta, Deepak Gupta:
Bipolar fuzzy based least squares twin bounded support vector machine. Fuzzy Sets Syst. 449: 120-161 (2022) - [j33]Deepak Gupta, Parashjyoti Borah, Usha Mary Sharma, Mukesh Prasad:
Data-driven mechanism based on fuzzy Lagrangian twin parametric-margin support vector machine for biomedical data analysis. Neural Comput. Appl. 34(14): 11335-11345 (2022) - [j32]Barenya Bikash Hazarika, Deepak Gupta:
Density Weighted Twin Support Vector Machines for Binary Class Imbalance Learning. Neural Process. Lett. 54(2): 1091-1130 (2022) - 2021
- [j31]Deepak Gupta, Bharat Richhariya:
Efficient implicit Lagrangian twin parametric insensitive support vector regression via unconstrained minimization problems. Ann. Math. Artif. Intell. 89(3-4): 301-332 (2021) - [j30]Parashjyoti Borah, Deepak Gupta:
Robust twin bounded support vector machines for outliers and imbalanced data. Appl. Intell. 51(8): 5314-5343 (2021) - [j29]Umesh Gupta, Deepak Gupta:
Least squares large margin distribution machine for regression. Appl. Intell. 51(10): 7058-7093 (2021) - [j28]Deepak Gupta, Umesh Gupta:
On robust asymmetric Lagrangian ν-twin support vector regression using pinball loss function. Appl. Soft Comput. 102: 107099 (2021) - [j27]Barenya Bikash Hazarika, Deepak Gupta, Parashjyoti Borah:
An intuitionistic fuzzy kernel ridge regression classifier for binary classification. Appl. Soft Comput. 112: 107816 (2021) - [j26]Bikram Kumar, Deepak Gupta:
Universum based Lagrangian twin bounded support vector machine to classify EEG signals. Comput. Methods Programs Biomed. 208: 106244 (2021) - [j25]Umesh Gupta, Deepak Gupta:
Kernel-Target Alignment Based Fuzzy Lagrangian Twin Bounded Support Vector Machine. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 29(5): 677-707 (2021) - [j24]Umesh Gupta, Deepak Gupta:
Regularized based implicit Lagrangian twin extreme learning machine in primal for pattern classification. Int. J. Mach. Learn. Cybern. 12(5): 1311-1342 (2021) - [j23]Deepak Gupta, Ambika Choudhury, Umesh Gupta, Priyanka Singh, Mukesh Prasad:
Computational approach to clinical diagnosis of diabetes disease: a comparative study. Multim. Tools Appl. 80(20): 30091-30116 (2021) - [j22]Debjyoti Das Adhikary, Deepak Gupta:
Applying over 100 classifiers for churn prediction in telecom companies. Multim. Tools Appl. 80(28-29): 35123-35144 (2021) - [j21]Barenya Bikash Hazarika, Deepak Gupta:
Density-weighted support vector machines for binary class imbalance learning. Neural Comput. Appl. 33(9): 4243-4261 (2021) - [j20]Umesh Gupta, Deepak Gupta:
On Regularization Based Twin Support Vector Regression with Huber Loss. Neural Process. Lett. 53(1): 459-515 (2021) - [c10]Shreya Pare, Mukesh Prasad, Deepak Puthal, Deepak Gupta, Anand Malik, Amit Saxena:
Multilevel Color Image Segmentation using Modified Fuzzy Entropy and Cuckoo Search Algorithm. FUZZ-IEEE 2021: 1-7 - 2020
- [j19]Amit Saxena, Shreya Pare, Mahendra Singh Meena, Deepak Gupta, Akshansh Gupta, Imran Razzak, Chin-Teng Lin, Mukesh Prasad:
A Two-Phase Approach for Semi-Supervised Feature Selection. Algorithms 13(9): 215 (2020) - [j18]Parashjyoti Borah, Deepak Gupta:
Unconstrained convex minimization based implicit Lagrangian twin extreme learning machine for classification (ULTELMC). Appl. Intell. 50(4): 1327-1344 (2020) - [j17]Barenya Bikash Hazarika, Deepak Gupta:
Modelling and forecasting of COVID-19 spread using wavelet-coupled random vector functional link networks. Appl. Soft Comput. 96: 106626 (2020) - [j16]Deepak Gupta, Kamalini Acharjee, Bharat Richhariya:
Lagrangian twin parametric insensitive support vector regression (LTPISVR). Neural Comput. Appl. 32(10): 5989-6007 (2020) - [j15]Parashjyoti Borah, Deepak Gupta:
Functional iterative approaches for solving support vector classification problems based on generalized Huber loss. Neural Comput. Appl. 32(13): 9245-9265 (2020) - [j14]Deepak Gupta, Barenya Bikash Hazarika, Mohanadhas Berlin:
Robust regularized extreme learning machine with asymmetric Huber loss function. Neural Comput. Appl. 32(16): 12971-12998 (2020) - [c9]Ahlam Alnefaie, Deepak Gupta, Monowar H. Bhuyan, Imran Razzak, Prashant Gupta, Mukesh Prasad:
End-to-End Analysis for Text Detection and Recognition in Natural Scene Images. IJCNN 2020: 1-8
2010 – 2019
- 2019
- [j13]Umesh Gupta, Deepak Gupta:
An improved regularization based Lagrangian asymmetric ν-twin support vector regression using pinball loss function. Appl. Intell. 49(10): 3606-3627 (2019) - [j12]Bharat Richhariya, Deepak Gupta:
Facial expression recognition using iterative universum twin support vector machine. Appl. Soft Comput. 76: 53-67 (2019) - [j11]Parashjyoti Borah, Deepak Gupta:
Unconstrained convex minimization based implicit Lagrangian twin random vector Functional-link networks for binary classification (ULTRVFLC). Appl. Soft Comput. 81 (2019) - [j10]Deepak Gupta, Bharat Richhariya, Parashjyoti Borah:
A fuzzy twin support vector machine based on information entropy for class imbalance learning. Neural Comput. Appl. 31(11): 7153-7164 (2019) - [c8]Deepak Gupta, Hemanga Jyoti Sarma, Kshitij Mishra, Mukesh Prasad:
Regularized Universum twin support vector machine for classification of EEG Signal. SMC 2019: 2298-2304 - 2018
- [j9]Deepak Gupta, Bharat Richhariya:
Entropy based fuzzy least squares twin support vector machine for class imbalance learning. Appl. Intell. 48(11): 4212-4231 (2018) - [c7]Mukesh Prasad, Liang-Cheng Chang, Deepak Gupta, Mahardhika Pratama, Suresh Sundaram, Chin-Teng Lin:
Online video streaming for human tracking based on weighted resampling particle filter. INNS Conference on Big Data 2018: 2-12 - [c6]Umesh Gupta, Deepak Gupta, Mukesh Prasad:
Kernel Target Alignment based Fuzzy Least Square Twin Bounded Support Vector Machine. SSCI 2018: 228-235 - [c5]Parashjyoti Borah, Deepak Gupta, Mukesh Prasad:
Improved 2-norm Based Fuzzy Least Squares Twin Support Vector Machine. SSCI 2018: 412-419 - [c4]Mukesh Prasad, Shantanu Rajora, Deepak Gupta, Yousef-Awwad Daraghmi, Eman Yasser Daraghmi, Pranay Yadav, Prayag Tiwari, Amit Saxena:
Fusion based En-FEC Transfer Learning Approach for Automobile Parts Recognition System. SSCI 2018: 2193-2199 - 2017
- [j8]S. Balasundaram, Deepak Gupta, Subhash Chandra Prasad:
A new approach for training Lagrangian twin support vector machine via unconstrained convex minimization. Appl. Intell. 46(1): 124-134 (2017) - [j7]Deepak Gupta:
Training primal K-nearest neighbor based weighted twin support vector regression via unconstrained convex minimization. Appl. Intell. 47(3): 962-991 (2017) - [c3]Kuang-Pen Chou, Mukesh Prasad, Deepak Gupta, Sharmi Sankar, Ting-Wei Xu, Suresh Sundaram, Chin-Teng Lin, Wen-Chieh Lin:
Block-based feature extraction model for early fire detection. SSCI 2017: 1-8 - [c2]Deepak Gupta, Parashjyoti Borah, Mukesh Prasad:
A fuzzy based Lagrangian twin parametric-margin support vector machine (FLTPMSVM). SSCI 2017: 1-7 - 2016
- [j6]S. Balasundaram, Deepak Gupta:
On optimization based extreme learning machine in primal for regression and classification by functional iterative method. Int. J. Mach. Learn. Cybern. 7(5): 707-728 (2016) - [j5]S. Balasundaram, Deepak Gupta:
Knowledge-based extreme learning machines. Neural Comput. Appl. 27(6): 1629-1641 (2016) - 2014
- [j4]S. Balasundaram, Deepak Gupta:
On implicit Lagrangian twin support vector regression by Newton method. Int. J. Comput. Intell. Syst. 7(1): 50-64 (2014) - [j3]S. Balasundaram, Deepak Gupta, Kapil:
1-Norm extreme learning machine for regression and multiclass classification using Newton method. Neurocomputing 128: 4-14 (2014) - [j2]S. Balasundaram, Deepak Gupta:
Training Lagrangian twin support vector regression via unconstrained convex minimization. Knowl. Based Syst. 59: 85-96 (2014) - [j1]S. Balasundaram, Deepak Gupta, Kapil:
Lagrangian support vector regression via unconstrained convex minimization. Neural Networks 51: 67-79 (2014) - 2013
- [c1]Deepak Gupta, Kewal Krishan Nailwal, Sameer Sharma:
A Heuristic for Permutation Flowshop Scheduling to Minimize Makespan. SocProS (2) 2013: 423-432
Coauthor Index
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last updated on 2024-07-09 23:40 CEST by the dblp team
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