Recognition Algorithm Based on Improved FCM and Rough Sets for Meibomian Gland Morphology

Liang, Fengmei; Xu, Yuelei; Li, Weixin; Ning, Xiaoling; Liu, Xueou; Liu, Ajian

doi:10.3390/app7020192

Cited by 12 publications

(7 citation statements)

References 19 publications

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“…Quantification of the area of meibomian glands loss is of importance when assessing MGD. To date, automatic methods based on image processing techniques have been developed for the automated assessment and classification of MGD (Arita et al, 2014;Celik et al, 2013;Koprowski et al, 2017;Liang et al, 2017;Llorens-Quintana et al, 2019;Pult and Riede-Pult, 2013;. In recent years, MGD automatic analysis methods based on convolutional neural network (CNN) have been developed rapidly.…”

Section: Conflict Of Interestmentioning

confidence: 99%

Artificial Intelligence Applications in Chronic Ocular Diseases

2024

Frontiers Research Topics

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Frontiers is more than just an open access publisher of scholarly articles: it is a pioneering approach to the world of academia, radically improving the way scholarly research is managed. The grand vision of Frontiers is a world where all people have an equal opportunity to seek, share and generate knowledge. Frontiers provides immediate and permanent online open access to all its publications, but this alone is not enough to realize our grand goals. Frontiers journal seriesThe Frontiers journal series is a multi-tier and interdisciplinary set of openaccess, online journals, promising a paradigm shift from the current review, selection and dissemination processes in academic publishing. All Frontiers journals are driven by researchers for researchers; therefore, they constitute a service to the scholarly community. At the same time, the Frontiers journal series operates on a revolutionary invention, the tiered publishing system, initially addressing specific communities of scholars, and gradually climbing up to broader public understanding, thus serving the interests of the lay society, too. Dedication to qualityEach Frontiers article is a landmark of the highest quality, thanks to genuinely collaborative interactions between authors and review editors, who include some of the world's best academicians. Research must be certified by peers before entering a stream of knowledge that may eventually reach the public -and shape society; therefore, Frontiers only applies the most rigorous and unbiased reviews. Frontiers revolutionizes research publishing by freely delivering the most outstanding research, evaluated with no bias from both the academic and social point of view. By applying the most advanced information technologies, Frontiers is catapulting scholarly publishing into a new generation. What are Frontiers Research Topics?Frontiers Research Topics are very popular trademarks of the Frontiers journals series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area.

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Section: Conflict Of Interestmentioning

confidence: 99%

Artificial Intelligence Applications in Chronic Ocular Diseases

2024

Frontiers Research Topics

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“…Rough sets can be used for pattern recognition and feature selection. They are used in several disciplines, such as finance [90,91], banking [92], engineering [93], medicine [94], etc. The data and their knowledge are associated, but variables with the same information are very indiscernible or similar.…”

Section: Rough Setsmentioning

confidence: 99%

Forecasting the Environmental, Social, and Governance Rating of Firms by Using Corporate Financial Performance Variables: A Rough Set Approach

et al. 2020

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The environmental, social, and governance (ESG) rating of firms is a useful tool for stakeholders and investment decision-makers. This paper develops a rough set model to relate ESG scores to popular corporate financial performance measures. This methodology permits handling with information in an uncertain, ambiguous, and imperfect context. A large database was gathered, including ESG scores, as well as industry sector and financial variables for publicly traded European companies during the period 2013–2018. We carried out 500 simulations of the rough set model for different values in the discretization parameter and different grouping scenarios of firms regarding ESG scores. The results suggest that the variables considered are useful in the prediction of ESG rank when firms are clustered in three or four equally balanced groups. However, the prediction power vanishes when a larger number of groups is computed. This would suggest that industry sector and financial variables serve to find big differences across firms regarding ESG, but the significance of the model drops when small differences in ESG performance are scrutinized.

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“…In [19], Liang et al proposed a new method to improve the state of the art in automatically judging meibomian gland morphology. The method is based on an improved fuzzy c-means (FCM) algorithm and rough sets theory.…”

Section: Smart Medicinementioning

confidence: 99%