Ankit Gupta

Scopus Publications

SiViS: Simulated multi-patient physiological clinical states for advanced vital sign radar monitoring research
Karla Miriam Reyes, Ankit Gupta, Arthur Grosmaire, Silvie Procházková, Petr Matouch, et al.
Scientific Data, 2026
RGB, a Surrogate of Infrared Facial Videos for Physiological Signs Estimations in Dark
Ankit Gupta, Antonio G. Ravelo-García, Fernando Morgado Dias
IEEE Transactions on Circuits and Systems for Video Technology, 2026
MARS lander: Georeferencing landing and pop points of untethered ocean monitoring systems using fundamental physics
Marko Radeta, Zahra Behboodi, Vladimir Zekovic, Décio Alves, David Pestana, et al.
Deep Sea Research Part I Oceanographic Research Papers, 2026
Radar Placement Effects on Multi-patient Heart and Respiration Monitoring, SiViS Dataset Validation
Karla Miriam Reyes Leiva, Ankit Gupta, Martin Cerny
Lecture Notes in Computer Science, 2026
Multi-Objective Undercomplete Independent Component Analysis for Radar Signals based Heart Rate and Interbeat Interval Estimations
Ankit Gupta, Karla Reyes, Martin Cerny
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society EMBS, 2025
Recent advancements in deep learning-based remote photoplethysmography methods
Ankit Gupta, Antonio G. Ravelo-García, Fernando Morgado-Dias
Data Fusion Techniques and Applications for Smart Healthcare, 2024
Review of deep learning techniques for power generation prediction of industrial solar photovoltaic plants
Shyam Singh Chandel, Ankit Gupta, Rahul Chandel, Salwan Tajjour
Solar Compass, 2023
Visual Explanations of Deep Learning Architectures in Predicting Cyclic Alternating Patterns Using Wavelet Transforms
Ankit Gupta, Fábio Mendonça, Sheikh Shanawaz Mostafa, Antonio G. Ravelo-García, Fernando Morgado-Dias
Electronics Switzerland, 2023
Cyclic Alternating Pattern (CAP) is a sleep instability marker defined based on the amplitude and frequency of the electroencephalogram signal. Because of the time and intensive process of labeling the data, different machine learning and automatic approaches are proposed. However, due to the low accuracy of the traditional approach and the black box approach of the machine learning approach, the proposed systems remain untrusted by the physician. This study contributes to accurately estimating CAP in a Frequency-Time domain by A-phase and its subtypes prediction by transforming the monopolar deviated electroencephalogram signals into corresponding scalograms. Subsequently, various computer vision classifiers were tested for the A-phase using scalogram images. It was found that MobileNetV2 outperformed all other tested classifiers by achieving the average accuracy, sensitivity, and specificity values of 0.80, 0.75, and 0.81, respectively. The MobileNetV2 trained model was further fine-tuned for A-phase subtypes prediction. To further verify the visual ability of the trained models, Gradcam++ was employed to identify the targeted regions by the trained network. It was verified that the areas identified by the model match the regions focused on by the sleep experts for A-phase predictions, thereby proving its clinical viability and robustness. This motivates the development of novel deep learning based methods for CAP patterns predictions.
Non-Destructive Banana Ripeness Detection Using Shallow and Deep Learning: A Systematic Review
Preety Baglat, Ahatsham Hayat, Fábio Mendonça, Ankit Gupta, Sheikh Shanawaz Mostafa, et al.
Sensors, 2023
The ripeness of bananas is the most significant factor affecting nutrient composition and demand. Conventionally, cutting and ripeness analysis requires expert knowledge and substantial human intervention, and different studies have been conducted to automate and substantially reduce human effort. Using the Preferred Reporting Items for the Systematic Reviews approach, 1548 studies were extracted from journals and conferences, using different research databases, and 35 were included in the final review for key parameters. These studies suggest the dominance of banana fingers as input data, a sensor camera as the preferred capturing device, and appropriate features, such as color, that can provide better detection. Among six stages of ripeness, the studies employing the four mentioned stages performed better in terms of accuracy and coefficient of determination value. Among all the works for detecting ripeness stages prediction, convolutional neural networks were found to perform sufficiently well with large datasets, whereas conventional artificial neural networks and support vector machines attained better performance for sensor-related data. However, insufficient information on the dataset and capturing device, limited data availability, and exploitation of data augmentation techniques are limitations in existing studies. Thus, effectively addressing these shortcomings and close collaboration with experts to predict the ripeness stages should be pursued.
A-phase index: an alternative view for sleep stability analysis based on automatic detection of the A-phases from the cyclic alternating pattern
Fábio Mendonça, Sheikh Shanawaz Mostafa, Ankit Gupta, Erna Sif Arnardottir, Timo Leppänen, et al.
Sleep, 2023
Study Objectives Sleep stability can be studied by evaluating the cyclic alternating pattern (CAP) in electroencephalogram (EEG) signals. The present study presents a novel approach for assessing sleep stability, developing an index based on the CAP A-phase characteristics to display a sleep stability profile for a whole night’s sleep. Methods Two ensemble classifiers were developed to automatically score the signals, one for “A-phase” and the other for “non-rapid eye movement” estimation. Both were based on three one-dimension convolutional neural networks. Six different inputs were produced from the EEG signal to feed the ensembles’ classifiers. A proposed heuristic-oriented search algorithm individually tuned the classifiers’ structures. The outputs of the two ensembles were combined to estimate the A-phase index (API). The models can also assess the A-phase subtypes, their API, and the CAP cycles and rate. Results Four dataset variations were considered, examining healthy and sleep-disordered subjects. The A-phase average estimation’s accuracy, sensitivity, and specificity range was 82%–87%, 72%–80%, and 82%–88%, respectively. A similar performance was attained for the A-phase subtype’s assessments, with an accuracy range of 82%–88%. Furthermore, in the examined dataset’s variations, the API metric’s average error varied from 0.15 to 0.25 (with a median range of 0.11–0.24). These results were attained without manually removing wake or rapid eye movement periods, leading to a methodology suitable to produce a fully automatic CAP scoring algorithm. Conclusions Metrics based on API can be understood as a new view for CAP analysis, where the goal is to produce and examine a sleep stability profile.
A Motion and Illumination Resistant Non-Contact Method Using Undercomplete Independent Component Analysis and Levenberg-Marquardt Algorithm
Ankit Gupta, Antonio G. Ravelo-Garcia, Fernando Morgado Dias
IEEE Journal of Biomedical and Health Informatics, 2022
An empirical investigation of market risk, dependence structure, and portfolio management between green bonds and international financial markets
Rimsha Ejaz, Sumaira Ashraf, Arshad Hassan, Ankit Gupta
Journal of Cleaner Production, 2022
Availability and performance of face based non-contact methods for heart rate and oxygen saturation estimations: A systematic review
Ankit Gupta, Antonio G. Ravelo-García, Fernando Morgado Dias
Computer Methods and Programs in Biomedicine, 2022
Computational approaches for malaria diagnosis using machine learning: A review
Mobile Health Advances in Research and Applications, 2021
Solving Image Processing Critical Problems Using Machine Learning
Ajay Sharma, Ankit Gupta, Varun Jaiswal
Studies in Big Data, 2021
Prediction of Alzheimer associated proteins (PAAP): A perspective to understand Alzheimer disease for therapeutic design
Gaurav Gupta, Neha Gupta, Ankit Gupta, Pankaj Vaidya, Girish Kumar Singh, et al.
International Journal of Bioinformatics Research and Applications, 2021
Multiple Machine Learning Models for Detection of Alzheimer’s Disease Using OASIS Dataset
Preety Baglat, Ahmad Waleed Salehi, Ankit Gupta, Gaurav Gupta
IFIP Advances in Information and Communication Technology, 2020
Application and Analysis of Hyperspectal Imaging
Ajay Sharma, Deep Kaur, Ankit Gupta, Varun Jaiswal
Proceedings of IEEE International Conference on Signal Processing Computing and Control, 2019
Machine learning based performance evaluation system based on multi-categorial factors
Kapil Sethi, Ankit Gupta, Varun Jaiswal
Pdgc 2018 2018 5th International Conference on Parallel Distributed and Grid Computing, 2018
A review and analysis of mobile health applications for alzheimer patients and caregivers
Gaurav Gupta, Ankit Gupta, Varun Jaiswal, Mohd Dilshad Ansari
Pdgc 2018 2018 5th International Conference on Parallel Distributed and Grid Computing, 2018
Machine Learning based Prediction of Anatomical Therapeutic Chemical (ATC) Class of Drug Like Molecule
Pankaj Vaidya, Ankit Gupta, Varun Jaiswal
2018 International Conference on Recent Innovations in Electrical Electronics and Communication Engineering Icrieece 2018, 2018
Hyperspectral imaging: A brief introduction for beginners
Smart Materials for Smart Living, 2017
Jenner-predict server: Prediction of protein vaccine candidates (PVCs) in bacteria based on host-pathogen interactions
Varun Jaiswal, Sree Krishna Chanumolu, Ankit Gupta, Rajinder S Chauhan, Chittaranjan Rout
BMC Bioinformatics, 2013

RECENT SCHOLAR PUBLICATIONS

MARS Lander: Georeferencing Landing and Pop Points of Untethered Ocean Monitoring Systems using Fundamental Physics
M Radeta, Z Behboodi, V Zekovic, D Alves, D Pestana, D Nunes, ...
Deep Sea Research Part I: Oceanographic Research Papers, 104650 , 2026
2026
RGB, a Surrogate of Infrared Facial Videos for Physiological Signs Estimations in Dark
A Gupta, AG Ravelo-García, FM Dias
IEEE Transactions on Circuits and Systems for Video Technology , 2026
2026
SiViS: Simulated multi-patient physiological clinical states for advanced vital sign radar monitoring research
KM Reyes, A Gupta, A Grosmaire, S Procházková, P Matouch, I Závacká, ...
Scientific Data , 2026
2026
Radar Placement Effects on Multi-patient Heart and Respiration Monitoring, SiViS Dataset Validation
KM Reyes Leiva, A Gupta, M Cerny
International Workshop on Sensor-Based Activity Recognition and Artificial … , 2025
2025
Multi-Objective Undercomplete Independent Component Analysis for Radar Signals based Heart Rate and Interbeat Interval Estimations
A Gupta, K Reyes, M Cerny
2025 47th Annual International Conference of the IEEE Engineering in … , 2025
2025
Facial video based physiological variables estimation in dark environments
A Gupta
2024
System and Method for Estimating at least One Physiological Sign of a Subject in Dark Environments
A Gupta, AG Ravelo-García, F Morgado-Dias
WO Patent WO/2024/246,626 , 2024
2024
Recent advancements in deep learning-based remote photoplethysmography methods
A Gupta, AG Ravelo-García, F Morgado-Dias
Data Fusion Techniques and Applications for Smart Healthcare, 127-155 , 2024
2024
Citations: 4
Review of deep learning techniques for power generation prediction of industrial solar photovoltaic plants
SS Chandel, A Gupta, R Chandel, S Tajjour
Solar Compass 8, 100061 , 2023
2023
Citations: 77
Visual explanations of deep learning architectures in predicting cyclic alternating patterns using wavelet transforms
A Gupta, F Mendonça, SS Mostafa, AG Ravelo-García, F Morgado-Dias
Electronics 12 (13), 2954 , 2023
2023
Citations: 2
Non-destructive banana ripeness detection using shallow and deep learning: A systematic review
P Baglat, A Hayat, F Mendonca, A Gupta, SS Mostafa, F Morgado-Dias
Sensors 23 (2), 738 , 2023
2023
Citations: 46
A-phase index: an alternative view for sleep stability analysis based on automatic detection of the A-phases from the cyclic alternating pattern
F Mendonça, SS Mostafa, A Gupta, ES Arnardottir, T Leppänen, ...
Sleep 46 (1), zsac217 , 2023
2023
Citations: 12
An empirical investigation of market risk, dependence structure, and portfolio management between green bonds and international financial markets
R Ejaz, S Ashraf, A Hassan, A Gupta
Journal of Cleaner Production 365, 132666 , 2022
2022
Citations: 55
Availability and performance of face based non-contact methods for heart rate and oxygen saturation estimations: A systematic review
A Gupta, AG Ravelo-Garcia, FM Dias
Computer methods and programs in biomedicine 219, 106771 , 2022
2022
Citations: 40
A motion and illumination resistant non-contact method using undercomplete independent component analysis and Levenberg-Marquardt algorithm
A Gupta, AG Ravelo-García, FM Dias
IEEE Journal of Biomedical and Health Informatics 26 (10), 4837-4848 , 2022
2022
Citations: 18
Solving image processing critical problems using machine learning
A Sharma, A Gupta, V Jaiswal
Machine Learning for Intelligent Multimedia Analytics: Techniques and … , 2021
2021
Citations: 19
Prediction of Alzheimer associated proteins (PAAP): A perspective to understand Alzheimer disease for therapeutic design
G Gupta, N Gupta, A Gupta, P Vaidya, GK Singh, V Jaiswal
International Journal of Bioinformatics Research and Applications 17 (4 … , 2021
2021
Citations: 5
Multiple machine learning models for detection of Alzheimer’s disease using OASIS dataset
P Baglat, AW Salehi, A Gupta, G Gupta
International Working Conference on Transfer and Diffusion of IT, 614-622 , 2020
2020
Citations: 66
Application and analysis of hyperspectal imaging
A Sharma, D Kaur, A Gupta, V Jaiswal
2019 5th International Conference on Signal Processing, Computing and … , 2019
2019
Citations: 19
Comparative analysis of machine learning algorithms on different datasets
K Sethi, A Gupta, G Gupta, V Jaiswal
Circulation in computer science international conference on innovations in … , 2019
2019
Citations: 32

MOST CITED SCHOLAR PUBLICATIONS

Jenner-predict server: prediction of protein vaccine candidates (PVCs) in bacteria based on host-pathogen interactions
V Jaiswal, SK Chanumolu, A Gupta, RS Chauhan, C Rout
BMC bioinformatics 14 (1), 211 , 2013
2013
Citations: 97
Review of deep learning techniques for power generation prediction of industrial solar photovoltaic plants
SS Chandel, A Gupta, R Chandel, S Tajjour
Solar Compass 8, 100061 , 2023
2023
Citations: 77
Multiple machine learning models for detection of Alzheimer’s disease using OASIS dataset
P Baglat, AW Salehi, A Gupta, G Gupta
International Working Conference on Transfer and Diffusion of IT, 614-622 , 2020
2020
Citations: 66
An empirical investigation of market risk, dependence structure, and portfolio management between green bonds and international financial markets
R Ejaz, S Ashraf, A Hassan, A Gupta
Journal of Cleaner Production 365, 132666 , 2022
2022
Citations: 55
Non-destructive banana ripeness detection using shallow and deep learning: A systematic review
P Baglat, A Hayat, F Mendonca, A Gupta, SS Mostafa, F Morgado-Dias
Sensors 23 (2), 738 , 2023
2023
Citations: 46
Availability and performance of face based non-contact methods for heart rate and oxygen saturation estimations: A systematic review
A Gupta, AG Ravelo-Garcia, FM Dias
Computer methods and programs in biomedicine 219, 106771 , 2022
2022
Citations: 40
A review and analysis of mobile health applications for Alzheimer patients and caregivers
G Gupta, A Gupta, V Jaiswal, MD Ansari
2018 Fifth International Conference on Parallel, Distributed and Grid … , 2018
2018
Citations: 39
Comparative analysis of machine learning algorithms on different datasets
K Sethi, A Gupta, G Gupta, V Jaiswal
Circulation in computer science international conference on innovations in … , 2019
2019
Citations: 32
Machine learning based performance evaluation system based on multi-categorial factors
K Sethi, A Gupta, V Jaiswal
2018 Fifth international conference on parallel, distributed and grid … , 2018
2018
Citations: 25
Solving image processing critical problems using machine learning
A Sharma, A Gupta, V Jaiswal
Machine Learning for Intelligent Multimedia Analytics: Techniques and … , 2021
2021
Citations: 19
Application and analysis of hyperspectal imaging
A Sharma, D Kaur, A Gupta, V Jaiswal
2019 5th International Conference on Signal Processing, Computing and … , 2019
2019
Citations: 19
Mobile health applications and android toolkit for alzheimer patients, caregivers and doctors
G Gupta, A Gupta, P Barura, V Jaiswal
Biological Forum–An International Journal 11 (1), 199-205 , 2019
2019
Citations: 19
A motion and illumination resistant non-contact method using undercomplete independent component analysis and Levenberg-Marquardt algorithm
A Gupta, AG Ravelo-García, FM Dias
IEEE Journal of Biomedical and Health Informatics 26 (10), 4837-4848 , 2022
2022
Citations: 18
A-phase index: an alternative view for sleep stability analysis based on automatic detection of the A-phases from the cyclic alternating pattern
F Mendonça, SS Mostafa, A Gupta, ES Arnardottir, T Leppänen, ...
Sleep 46 (1), zsac217 , 2023
2023
Citations: 12
Machine learning based prediction of anatomical therapeutic chemical (ATC) class of drug like molecule
P Vaidya, A Gupta, V Jaiswal
2018 International Conference on Recent Innovations in Electrical … , 2018
2018
Citations: 10
Conserved HIV wide spectrum antipeptides-a hope for HIV treatment
BS Rao, KK Gupta, S Kumari, A Gupta, K Pujitha
Adv Tech Biol Med 1 (102), 2379-1764.1000102 , 2013
2013
Citations: 8
Prediction of Alzheimer associated proteins (PAAP): A perspective to understand Alzheimer disease for therapeutic design
G Gupta, N Gupta, A Gupta, P Vaidya, GK Singh, V Jaiswal
International Journal of Bioinformatics Research and Applications 17 (4 … , 2021
2021
Citations: 5
Recent advancements in deep learning-based remote photoplethysmography methods
A Gupta, AG Ravelo-García, F Morgado-Dias
Data Fusion Techniques and Applications for Smart Healthcare, 127-155 , 2024
2024
Citations: 4
A comparative analysis of tensor decomposition models using hyper spectral image
A Gupta, A Oberoi
arXiv preprint arXiv:1503.06561 , 2015
2015
Citations: 4
Visual explanations of deep learning architectures in predicting cyclic alternating patterns using wavelet transforms
A Gupta, F Mendonça, SS Mostafa, AG Ravelo-García, F Morgado-Dias
Electronics 12 (13), 2954 , 2023
2023
Citations: 2

Ankit Gupta

RESEARCH, TEACHING, or OTHER INTERESTS

Scopus Publications

RECENT SCHOLAR PUBLICATIONS

MOST CITED SCHOLAR PUBLICATIONS