Review of constraints on vision‐based gesture recognition for human–computer interaction

BK Chakraborty, D Sarma, MK Bhuyan… - IET Computer …, 2018‏ - Wiley Online Library
The ability of computers to recognise hand gestures visually is essential for progress in
human–computer interaction. Gesture recognition has applications ranging from sign …

Methods, databases and recent advancement of vision-based hand gesture recognition for hci systems: A review

D Sarma, MK Bhuyan - SN Computer Science, 2021‏ - Springer
Hand gesture recognition is viewed as a significant field of exploration in computer vision
with assorted applications in the human–computer communication (HCI) community. The …

An interpretable dynamic inference system based on fuzzy broad learning

H Zhao, Y Wu, W Deng - IEEE Transactions on Instrumentation …, 2023‏ - ieeexplore.ieee.org
Fuzzy broad learning system (FBLS) is a fuzzy neural model proposed in recent years,
which combines the efficient performance of broad learning and the interpretability of fuzzy …

Deep Takagi–Sugeno–Kang fuzzy classifier with shared linguistic fuzzy rules

Y Zhang, H Ishibuchi, S Wang - IEEE Transactions on Fuzzy …, 2017‏ - ieeexplore.ieee.org
In many practical applications of classifiers, not only high accuracy but also high
interpretability is required. Among a wide variety of existing classifiers, Takagi–Sugeno …

A multiple-kernel fuzzy c-means algorithm for image segmentation

L Chen, CLP Chen, M Lu - IEEE Transactions on Systems, Man …, 2011‏ - ieeexplore.ieee.org
In this paper, a generalized multiple-kernel fuzzy C-means (FCM)(MKFCM) methodology is
introduced as a framework for image-segmentation problems. In the framework, aside from …

Knowledge-leverage-based TSK fuzzy system modeling

Z Deng, Y Jiang, KS Choi, FL Chung… - IEEE transactions on …, 2013‏ - ieeexplore.ieee.org
Classical fuzzy system modeling methods consider only the current scene where the training
data are assumed to be fully collectable. However, if the data available from the current …

On the accuracy–complexity tradeoff of fuzzy broad learning system

S Feng, CLP Chen, L Xu, Z Liu - IEEE Transactions on Fuzzy …, 2020‏ - ieeexplore.ieee.org
The fuzzy broad learning system (FBLS) is a recently proposed neuro-fuzzy model that
shares the similar structure of a broad learning system (BLS). It shows high accuracy in both …

Multitask TSK fuzzy system modeling by mining intertask common hidden structure

Y Jiang, FL Chung, H Ishibuchi… - IEEE transactions on …, 2014‏ - ieeexplore.ieee.org
The classical fuzzy system modeling methods implicitly assume data generated from a
single task, which is essentially not in accordance with many practical scenarios where data …

A comprehensive adaptive interpretable takagi-sugeuo-kang fuzzy classifier for fatigue driving detection

D Gao, S Liu, Y Gao, P Li, H Zhang… - … on Fuzzy Systems, 2024‏ - ieeexplore.ieee.org
Electroencephalogram (EEG) signals, as a reliable biological indicator, have been widely
used in fatigue driving detection due to their capacity to reflect a driver's cognitive and neural …

Broad learning based dynamic fuzzy inference system with adaptive structure and interpretable fuzzy rules

K Bai, X Zhu, S Wen, R Zhang… - IEEE Transactions on …, 2021‏ - ieeexplore.ieee.org
This article investigates the feasibility of applying the broad learning system (BLS) to realize
a novel Takagi–Sugeno–Kang (TSK) neuro-fuzzy model, namely a broad learning based …