@inproceedings{98ae5cf058984951962a255d95de54ae,
title = "Meme Kanserinde CerbB2 T{\"u}m{\"o}r H{\"u}crelerinin Siniflandirilmasi i{\c c}in Derin {\"O}ǧrenme Tabanli Bir Yakla{\c s}im",
abstract = "This study proposes a unique approach to classify CerbB2 tumor cell scores in breast cancer based on deep learning models. Another contribution of the study is the creation of a dataset from original breast cancer tissues. On the purpose of training, validating and testing with deep learning models cell fragments were generated from sample tissue images. CerbB2 tumor scores were generated for the cell fragments were classified with high performance by the aid of convolutional neural networks (CNN).",
keywords = "CerbB2 marker, classification, Convolutional Neural Networks (CNN), score, tumor",
author = "Tataroglu, {Gozde A.} and Anil Genc and Kabakci, {Kaan A.} and Abdulkerim Capar and Toreyin, {B. Ugur} and Ekenel, {Hazim K.} and Ilknur Turkmen and Asli Cakir",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 25th Signal Processing and Communications Applications Conference, SIU 2017 ; Conference date: 15-05-2017 Through 18-05-2017",
year = "2017",
month = jun,
day = "27",
doi = "10.1109/SIU.2017.7960587",
language = "Undefined",
series = "2017 25th Signal Processing and Communications Applications Conference, SIU 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2017 25th Signal Processing and Communications Applications Conference, SIU 2017",
}