Zobrazeno 1 - 10
of 22
pro vyhledávání: '"S. V. Aruna Kumar"'
Publikováno v:
Applied Sciences, Vol 12, Iss 15, p 7385 (2022)
Brain tissue segmentation is an important component of the clinical diagnosis of brain diseases using multi-modal magnetic resonance imaging (MR). Brain tissue segmentation has been developed by many unsupervised methods in the literature. The most c
Externí odkaz:
https://doaj.org/article/036eb46b379941858d7b22299271eb88
Autor:
Matej Vitek, Abhijit Das, Diego Rafael Lucio, Luiz Antonio Zanlorensi, David Menotti, Jalil Nourmohammadi Khiarak, Mohsen Akbari Shahpar, Meysam Asgari-Chenaghlu, Farhang Jaryani, Juan E. Tapia, Andres Valenzuela, Caiyong Wang, Yunlong Wang, Zhaofeng He, Zhenan Sun, Fadi Boutros, Naser Damer, Jonas Henry Grebe, Arjan Kuijper, Kiran Raja, Gourav Gupta, Georgios Zampoukis, Lazaros Tsochatzidis, Ioannis Pratikakis, S. V. Aruna Kumar, B. S. Harish, Umapada Pal, Peter Peer, Vitomir Struc
Publikováno v:
IEEE Transactions on Information Forensics and Security. 18:190-205
Bias and fairness of biometric algorithms have been key topics of research in recent years, mainly due to the societal, legal and ethical implications of potentially unfair decisions made by automated decision-making models. A considerable amount of
Publikováno v:
International Journal of Natural Computing Research. 10:1-14
This article performs the sclera segmentation task by proposing a new hybrid symbolic fuzzy c-means (HSFCM) clustering method. Practically, though the data point exhibits some sort of similarity, unfortunately they are not undistinguishable and exhib
Publikováno v:
IEEE Transactions on Information Forensics and Security. 16:1696-1708
Over the years, unmanned aerial vehicles (UAVs) have been regarded as a potential solution to surveil public spaces, providing a cheap way for data collection, while covering large and difficult-to-reach areas. This kind of solutions can be particula
Publikováno v:
Augmented Intelligence in Healthcare: A Pragmatic and Integrated Analysis ISBN: 9789811910753
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::50c6eb7ef6436c62c324a457faef9d96
https://doi.org/10.1007/978-981-19-1076-0_21
https://doi.org/10.1007/978-981-19-1076-0_21
Autor:
B. S. Harish, S. V. Aruna Kumar
Publikováno v:
Journal of Intelligent Systems, Vol 27, Iss 4, Pp 593-607 (2018)
This paper presents a modified intuitionistic fuzzy clustering (IFCM) algorithm for medical image segmentation. IFCM is a variant of the conventional fuzzy C-means (FCM) based on intuitionistic fuzzy set (IFS) theory. Unlike FCM, IFCM considers both
Publikováno v:
Applied Sciences, Vol 10, Iss 5608, p 5608 (2020)
Applied Sciences
Volume 10
Issue 16
Applied Sciences
Volume 10
Issue 16
Human Attribute Recognition (HAR) is a highly active research field in computer vision and pattern recognition domains with various applications such as surveillance or fashion. Several approaches have been proposed to tackle the particular challenge
Publikováno v:
Procedia Computer Science. 132:1503-1511
A sequential learning framework for text categorization based on Meta-cognitive Neural Network (McNN) is presented in this paper. Initially text documents are pre-processed and represented in the form of Term Document Matrix (TDM). Since the TDM is o
Publikováno v:
Procedia Computer Science. 143:133-140
This paper presents an robust and efficient unsupervised method for ECG arrhythmia classification. The proposed method consists of two steps: feature selection and clustering. In proposed method, initially the input ECG data is fed into feature selec
Publikováno v:
Third International Workshop on Pattern Recognition.
This paper presents automatic ECG arrhythmia classification method using symbolic dynamics through hybrid classifier. The proposed method consists of four steps: pre-processing, data extraction, symbolic time series construction and classification. I