Zobrazeno 1 - 10 of 46 pro vyhledávání: '"J. Somasekar"'
1
Akademický článek
Ophthatome™: an integrated knowledgebase of ophthalmic diseases for translating vision research into the clinic
Autor: Praveen Raj, Sushma Tejwani, Dandayudhapani Sudha, B. Muthu Narayanan, Chandrasekar Thangapandi, Sankar Das, J. Somasekar, Susmithasane Mangalapudi, Durgesh Kumar, Narendra Pindipappanahalli, Rohit Shetty, Arkasubhra Ghosh, Govindasamy Kumaramanickavel, Amitabha Chaudhuri, Nagasamy Soumittra
Publikováno v: BMC Ophthalmology, Vol 20, Iss 1, Pp 1-11 (2020)
Abstract Background Medical big data analytics has revolutionized the human healthcare system by introducing processes that facilitate rationale clinical decision making, predictive or prognostic modelling of the disease progression and management, d
Externí odkaz: https://doaj.org/article/6e90d3688f4544e2bcdc159d2bc61cd6
Zobrazit plný text záznamu
2
Akademický článek
A dataset for automatic contrast enhancement of microscopic malaria infected blood RGB images
Autor: J. Somasekar, G. Ramesh, Gandikota Ramu, P. Dileep Kumar Reddy, B. Eswara Reddy, Ching-Hao Lai
Publikováno v: Data in Brief, Vol 27, Iss , Pp - (2019)
In this article we introduce a malaria infected microscopic images dataset for contrast enhancement which assist for malaria diagnosis more accurately. The dataset contains around two hundred malaria infected, normal, species and various stages of mi
Externí odkaz: https://doaj.org/article/83fb1bf4d41a476b8ce38894ac80f4ed
Zobrazit plný text záznamu
6
Border Detection of Malaria Infected Cells in Microscopic Images for Diagnosis: A Computer Vision Approach
Autor: J. Somasekar, Y. C. A. Padmanabha Reddy, Gajula Ramesh
Publikováno v: Journal of Computational and Theoretical Nanoscience. 17:4643-4647
A computer vision approach is presented for border detection of malaria infected cells in microscopic blood images for accurate diagnosis. First, the microscopic 24-bits RGB color blood image converted in to 8-bits gray scale image for a single chann
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::a9516e703c81a9a95464b80e0b59f133
https://doi.org/10.1166/jctn.2020.9292
Zobrazit plný text záznamu
9
WITHDRAWN: Improving the accuracy of heart attack risk prediction based on information gain feature selection technique
Autor: J. Somasekar, P. Dileep Kumar Reddy, Karanam Madhavi, Gattu Ramesh, Joseph Tan
Publikováno v: Materials Today: Proceedings.
Early prediction of heart disease helps in improving the health of patients with corrective measures. Machine learning (ML) based data-driven approaches are found to be viable alternatives. However, such machine learning algorithms suffer from data r
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::10294993195287b5ce4591480bafff0c
https://doi.org/10.1016/j.matpr.2020.12.079
Zobrazit plný text záznamu
10
WITHDRAWN: Machine learning and image analysis applications in the fight against COVID-19 pandemic: Datasets, research directions, challenges and opportunities
Autor: Avinash Sharma, J. Somasekar, Gattu Ramesh, P Pavan Kumar Visulaization
Publikováno v: Materials Today. Proceedings
Highlights • Machine Learning and Image Analysis techniques are a great way to help in diagnosis and prognosis of COVID-19 pandemic. • The time series forecasting of disease spread and case fatality rate (CFR) by using deep neural networks propos
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::09ba304c23ccb7c01b299951aad55587
https://doi.org/10.1016/j.matpr.2020.09.352
Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání

Omezení vyhledávání
Plný text Recenzováno Digitální knihovna AV ČR
Zdroje