| A survey on medical diagnosis of diabetes using machine learning techniques A Choudhury, D Gupta Recent Developments in Machine Learning and Data Analytics: IC3 2018, 67-78, 2019 | 143 | 2019 |
| Modelling and forecasting of COVID-19 spread using wavelet-coupled random vector functional link networks BB Hazarika, D Gupta Applied Soft Computing 96, 106626, 2020 | 115 | 2020 |
| Leaf disease detection using machine learning and deep learning: Review and challenges C Sarkar, D Gupta, U Gupta, BB Hazarika Applied Soft Computing 145, 110534, 2023 | 101 | 2023 |
| Density-weighted support vector machines for binary class imbalance learning BB Hazarika, D Gupta Neural Computing and Applications 33 (9), 4243-4261, 2021 | 97 | 2021 |
| A fuzzy twin support vector machine based on information entropy for class imbalance learning D Gupta, B Richhariya, P Borah Neural Computing and Applications, 1-12, 2018 | 89 | 2018 |
| 1-Norm extreme learning machine for regression and multiclass classification using Newton method S Balasundaram, D Gupta Neurocomputing 128, 4-14, 2014 | 75 | 2014 |
| Robust regularized extreme learning machine with asymmetric Huber loss function D Gupta, BB Hazarika, M Berlin Neural Computing and Applications 32 (16), 12971-12998, 2020 | 69 | 2020 |
| Artificial intelligence for suspended sediment load prediction: a review D Gupta, BB Hazarika, M Berlin, UM Sharma, K Mishra Environmental earth sciences 80 (9), 346, 2021 | 65 | 2021 |
| Facial expression recognition using iterative universum twin support vector machine B Richhariya, D Gupta Applied Soft Computing 76, 53-67, 2019 | 63 | 2019 |
| Modeling suspended sediment load in a river using extreme learning machine and twin support vector regression with wavelet conjunction BB Hazarika, D Gupta, M Berlin Environmental Earth Sciences 79 (10), 234, 2020 | 60 | 2020 |
| Entropy based fuzzy least squares twin support vector machine for class imbalance learning D Gupta, B Richhariya Applied Intelligence 48 (11), 4212-4231, 2018 | 58 | 2018 |
| An intuitionistic fuzzy kernel ridge regression classifier for binary classification BB Hazarika, D Gupta, P Borah Applied Soft Computing 112, 107816, 2021 | 54 | 2021 |
| On optimization based extreme learning machine in primal for regression and classification by functional iterative method S Balasundaram, D Gupta International Journal of Machine Learning and Cybernetics 7, 707-728, 2016 | 51 | 2016 |
| Training Lagrangian twin support vector regression via unconstrained convex minimization S Balasundaram, D Gupta Knowledge-Based Systems 59, 85-96, 2014 | 49 | 2014 |
| Lagrangian support vector regression via unconstrained convex minimization S Balasundaram, D Gupta Neural networks 51, 67-79, 2014 | 43 | 2014 |
| Streamflow prediction in mountainous region using new machine learning and data preprocessing methods: a case study RMA Ikram, BB Hazarika, D Gupta, S Heddam, O Kisi Neural Computing and Applications 35 (12), 9053-9070, 2023 | 42 | 2023 |
| Applying over 100 classifiers for churn prediction in telecom companies DD Adhikary, D Gupta Multimedia Tools and Applications 80 (28), 35123-35144, 2021 | 40 | 2021 |
| Universum based Lagrangian twin bounded support vector machine to classify EEG signals B Kumar, D Gupta Computer methods and programs in biomedicine 208, 106244, 2021 | 40 | 2021 |
| Robust twin bounded support vector machines for outliers and imbalanced data P Borah, D Gupta Applied Intelligence 51 (8), 5314-5343, 2021 | 40 | 2021 |
| On robust asymmetric Lagrangian ν-twin support vector regression using pinball loss function D Gupta, U Gupta Applied Soft Computing 102, 107099, 2021 | 38 | 2021 |
Dr Barenya Bikash HazarikaAssistant ProfessorVerified email at adtu.in
