Optimal estimation of SoC, SoH using machine learning models and design of control algorithm for active cell balancing in lithium ion batteries.

Autor: K, Sabeena Beevi, S, Abhishek, L, Mahima, G, Naveen Ram C, M, Parvati, P B, Adithyan, S, Sonu

Publikováno v: Engineering Research Express; Dec2024, Vol. 6 Issue 4, p1-14, 14p

A Multi-Classifier System for Automatic Mitosis Detection in Breast Histopathology Images Using Deep Belief Networks

Autor: K. Sabeena Beevi, Madhu S. Nair, G. R. Bindu

Publikováno v: IEEE Journal of Translational Engineering in Health and Medicine, Vol 5, Pp 1-11 (2017)

Mitotic count is an important diagnostic factor in breast cancer grading and prognosis. Detection of mitosis in breast histopathology images is very challenging mainly due to diffused intensities along object boundary and shape variation in different

Externí odkaz: https://doaj.org/article/9089423388244f2abaa9f52ae060d7ac

Trend Prediction of Power Transformers from DGA Data Using Artificial Intelligence Techniques

Autor: A. S. Kunju Lekshmi, Deepa S. Kumar, K. Sabeena Beevi

Publikováno v: Communication and Intelligent Systems ISBN: 9789811921292

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d6556142d6ccfa0f567f1754070be7d3
https://doi.org/10.1007/978-981-19-2130-8_81

Automatic mitosis detection in breast histopathology images using Convolutional Neural Network based deep transfer learning

Autor: Madhu S. Nair, G. R. Bindu, K. Sabeena Beevi

Publikováno v: Biocybernetics and Biomedical Engineering. 39:214-223

The exact measure of mitotic count is one of the crucial parameters in breast cancer grading and prognosis. Detection of mitosis in standard H & E stained histopathology images is challenging due to diffused intensities along object boundaries and sh

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::af5ba15799f69372fa1d1fa6c58e242a
https://doi.org/10.1016/j.bbe.2018.10.007

A Multi-Classifier System for Automatic Mitosis Detection in Breast Histopathology Images Using Deep Belief Networks

Autor: G. R. Bindu, K. Sabeena Beevi, Madhu S. Nair

Publikováno v: IEEE Journal of Translational Engineering in Health and Medicine, Vol 5, Pp 1-11 (2017)
IEEE Journal of Translational Engineering in Health and Medicine

Mitotic count is an important diagnostic factor in breast cancer grading and prognosis. Detection of mitosis in breast histopathology images is very challenging mainly due to diffused intensities along object boundary and shape variation in different

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::94777f8eb9dc643a1d540d5fe9ea1461
https://ieeexplore.ieee.org/document/7911274/