Bipolar fuzzy based least squares twin bounded support vector machine

U Gupta, D Gupta - Fuzzy Sets and Systems, 2022 - Elsevier
Data classification is a key domain of research in real-world applications. One of the big
challenges of real-world data classification is to tackle the presence of noise and outliers. In …

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

D Gupta, U Gupta - Applied Soft Computing, 2021 - Elsevier
The main objective of twin support vector regression (TSVR) is to find the optimum
regression function based on the ε-insensitive up-and down-bound with equal influences on …

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

D Gupta, A Choudhury, U Gupta, P Singh… - Multimedia Tools and …, 2021 - Springer
Diabetes is one of the most prevalent non-communicable diseases and is the 6th leading
cause of death worldwide. It'sa chronic metabolic disorder which has no cure, however, it is …

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

D Gupta, U Gupta, HJ Sarma - Multimedia Tools and Applications, 2024 - Springer
Due to the increasing popularity of support vector machine (SVM) and the introduction of
Universum, many variants of SVM along with Universum such as Universum support vector …

Analysis of randomization-based approaches for autism spectrum disorder

U Gupta, D Gupta, U Agarwal - Pattern Recognition and Data Analysis with …, 2022 - Springer
Autism spectrum disorder (ASD) is a severe neurodevelopmental disorder that affects an
individual's sensory activity, social interaction, and cognitive abilities. In the mental illnesses …

Kernel-target alignment based fuzzy Lagrangian twin bounded support vector machine

U Gupta, D Gupta - … of Uncertainty, Fuzziness and Knowledge-Based …, 2021 - World Scientific
To improve the generalization performance, we develop a new technique for handling the
impacts of outliers using Lagrangian twin bounded SVM (TBSVM) with kernel fuzzy …

Analysis of different tracking algorithms applied on thermal infrared imagery for maritime surveillance systems

AAS AlMansoori, I Swamidoss… - Artificial Intelligence …, 2020 - spiedigitallibrary.org
Maritime surveillance contributes in the security of ports, oil platforms, and coastal littoral by
detecting unusual activities such as unlicensed fishing boats, pirate attacks, and human …

An Improved Hybrid Model for Target Detection

U Gupta, R Golash, V Vats… - … Conference on Emerging …, 2023 - ieeexplore.ieee.org
Target Detection has entered into various practical implementations in various fields,
including healthcare, military and defense, autonomous driving, pedestrian detection …

Designing a Deep Learning Model

J Kukade, P Panse - … : Proceedings of ICT4SD 2023, Volume 2, 2023 - books.google.com
Anomaly detection in surveillance videos is a crucial task for ensuring public safety and
security. Traditional methods rely on rule-based or handcrafted feature-based approaches …

Automatic credit card approval prediction system

A Bhaskar, R Rani, G Jaiswal, A Dev… - AIP Conference …, 2024 - pubs.aip.org
Within the banking industry, requests for credit cards are growing tremendously, and
manually reviewing each application is frequently a tiresome task that is also prone to …