Deepak Gupta

2.9k citations

99 papers · 2.3k · 1 hit paper · h-index 28

Impact in

Artificial Intelligence top 1%
- Machine Learning and ELM
- Machine Learning and Data Classification
- Imbalanced Data Classification Techniques
- Neural Networks and Applications
Environmental Engineering top 5%
- Hydrological Forecasting Using AI

Papers in

Artificial Intelligence 70
- Machine Learning and ELM 55
- Machine Learning and Data Classification 25
- Imbalanced Data Classification Techniques 13
- Neural Networks and Applications 10
- Fuzzy Logic and Control Systems 6
Environmental Engineering 10
- Hydrological Forecasting Using AI 9

Co-authors: Barenya Bikash Hazarika (35 shared papers)Umesh Chandra Gupta (18 shared papers)Parashjyoti Borah (18 shared papers)Bharat Richhariya (7 shared papers)Sadhu Ramakrishnan Balasundaram (6 shared papers)Berlin Mohanadhas (7 shared papers)Narayanan Natarajan (5 shared papers)Mukesh Prasad (12 shared papers)
Journals: Applied Soft Computing (9 papers)Neural Computing and Applications (9 papers)Applied Intelligence (8 papers)Multimedia Tools and Applications (5 papers)Computers & Electrical Engineering (4 papers)
Partner nations: India Australia Singapore

In The Last Decade

Deepak Gupta

95 papers receiving 2.2k citations

Deepak Gupta's Hit Papers

align trajectories log scale

Leaf disease detection using machine learning and deep learning: Review and challenges 2023 · 166 citations

What are hit papers?

Paper score: A paper's citations measured against the top-1% bar of its own field and year: the square root of citations ÷ bar, so 1 means right at the bar and 2 means four times its citations. The bar blends the citation counts that enter the top 1% of the paper's subfields in its year (weighted 89.5%), of those subfields over all years (0.5%) and of its year across all fields (10%); a subfield and year with fewer than 400 papers takes its year's bar. Papers from 2026 are not scored yet: in an unfinished year, when a paper appeared matters more than how it is cited.

Hit paper: A paper cited at least 1.5× the top-1% bar of its field and year: a paper score of at least √1.5.

2023 Applied Soft Computing

Peers

Countries citing papers authored by Deepak Gupta

Since Specialization

Citations

This map shows the geographic impact of Deepak Gupta's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Deepak Gupta with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Deepak Gupta more than expected).

Fields of papers citing papers by Deepak Gupta

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Deepak Gupta. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Deepak Gupta. The network helps show where Deepak Gupta may publish in the future.

Co-authors

The 25 scholars most cited alongside Deepak Gupta, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Deepak Gupta Line = papers co-authored together Deepak Gupta links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

Showing the 20 most-cited of 99 papers — load more, or switch the sort, to bring in the rest.

#	Work
1	Leaf disease detection using machine learning and deep learning: Review and challenges Applied Soft Computing ·Chittabarni Sarkar, Deepak Gupta, Umesh Chandra Gupta, Barenya Bikash Hazarika Hit paper breakdown →	2023	166
2	Modelling and forecasting of COVID-19 spread using wavelet-coupled random vector functional link networks Applied Soft Computing ·Barenya Bikash Hazarika, Deepak Gupta	2020	94
3	A Survey on Medical Diagnosis of Diabetes Using Machine Learning Techniques Advances in intelligent systems and computing ·Ambika Choudhury, Deepak Gupta	2018	88
4	Density-weighted support vector machines for binary class imbalance learning Neural Computing and Applications ·Barenya Bikash Hazarika, Deepak Gupta	2020	87
5	A fuzzy twin support vector machine based on information entropy for class imbalance learning Neural Computing and Applications ·Deepak Gupta, Bharat Richhariya, Parashjyoti Borah	2018	77
6	Artificial intelligence for suspended sediment load prediction: a review Environmental Earth Sciences ·Deepak Gupta, Barenya Bikash Hazarika, Berlin Mohanadhas, Usha Mary Sharma +1 other	2021	64
7	Robust regularized extreme learning machine with asymmetric Huber loss function Neural Computing and Applications ·Deepak Gupta, Barenya Bikash Hazarika, Berlin Mohanadhas	2020	63
8	1-Norm extreme learning machine for regression and multiclass classification using Newton method Neurocomputing ·Sadhu Ramakrishnan Balasundaram, Deepak Gupta, Kapil	2013	56
9	An intuitionistic fuzzy kernel ridge regression classifier for binary classification Applied Soft Computing ·Barenya Bikash Hazarika, Deepak Gupta, Parashjyoti Borah	2021	55
10	Facial expression recognition using iterative universum twin support vector machine Applied Soft Computing ·Bharat Richhariya, Deepak Gupta	2018	54
11	Modeling suspended sediment load in a river using extreme learning machine and twin support vector regression with wavelet conjunction Environmental Earth Sciences ·Barenya Bikash Hazarika, Deepak Gupta, Berlin Mohanadhas	2020	54
12	Financial time series forecasting using twin support vector regression PLoS ONE ·Deepak Gupta, Mahardhika Pratama, Zhenyuan Ma, Jun Li, Mukesh Prasad	2019	51
13	Entropy based fuzzy least squares twin support vector machine for class imbalance learning Applied Intelligence ·Deepak Gupta, Bharat Richhariya	2018	49
14	On optimization based extreme learning machine in primal for regression and classification by functional iterative method International Journal of Machine Learning and Cybernetics ·Sadhu Ramakrishnan Balasundaram, Deepak Gupta	2014	46
15	Training Lagrangian twin support vector regression via unconstrained convex minimization Knowledge-Based Systems ·Sadhu Ramakrishnan Balasundaram, Deepak Gupta	2014	44
16	Robust twin bounded support vector machines for outliers and imbalanced data Applied Intelligence ·Parashjyoti Borah, Deepak Gupta	2021	40
17	Lagrangian support vector regression via unconstrained convex minimization Neural Networks ·Deepak Gupta, Kapil +1 other	2013	39
18	Density Weighted Twin Support Vector Machines for Binary Class Imbalance Learning Neural Processing Letters ·Barenya Bikash Hazarika, Deepak Gupta	2021	38
19	Universum based Lagrangian twin bounded support vector machine to classify EEG signals Computer Methods and Programs in Biomedicine ·Deepak Gupta +1 other	2021	38
20	Comparison of machine learning and deep learning techniques for the prediction of air pollution: a case study from China Asian Journal of Atmospheric Environment ·Ishan Ayus, Narayanan Natarajan, Deepak Gupta	2023	38

About Deepak Gupta

Deepak Gupta is a scholar working on Artificial Intelligence, Environmental Engineering, Information Systems, Computer Vision and Pattern Recognition and Health Information Management, having authored 99 papers that have together received 2.3k indexed citations. Recurring topics across this work include Machine Learning and ELM (55 papers), Machine Learning and Data Classification (25 papers), Imbalanced Data Classification Techniques (13 papers), Neural Networks and Applications (10 papers), Data Mining and Machine Learning Applications (10 papers), Hydrological Forecasting Using AI (9 papers), Fuzzy Logic and Control Systems (6 papers) and Artificial Intelligence in Healthcare (3 papers). The work is most often cited by research in Artificial Intelligence (1k citations), Environmental Engineering (215 citations), Health Information Management (126 citations), Computational Mathematics (5 citations) and Modeling and Simulation (34 citations). Deepak Gupta has collaborated with scholars based in India, Australia and Singapore. Frequent co-authors include Barenya Bikash Hazarika, Umesh Chandra Gupta, Parashjyoti Borah, Bharat Richhariya, Sadhu Ramakrishnan Balasundaram, Berlin Mohanadhas, Narayanan Natarajan, Mukesh Prasad, Usha Mary Sharma and Mahardhika Pratama. Their work appears in journals such as Applied Soft Computing, Neural Computing and Applications, Applied Intelligence, Multimedia Tools and Applications and Computers & Electrical Engineering.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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Deepak Gupta

Deepak Gupta's Hit Papers

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About Deepak Gupta

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