Natnael Tilahun Sinshaw

Work place: Department of Software Engineering, CoE for HPC and BDA, AASTU, Addis Ababa, Ethiopia



Research Interests:


Natnael Tilahun Sinshaw earned a BSc in Computer Science and Information Technology on January 28, 2018, and MSc in Software Engineering on January 28, 2021, both from Addis Ababa Science and Technology University (AASTU) in Addis Ababa, Ethiopia. He has worked as an Academic Research Assistant at AASTU in Addis Ababa, Ethiopia from September 11, 2018 up to September 5, 2020. Currently, he is working as a Computer Science instructor at CPU college, Addis Ababa, Ethiopia. Additionally, he’s a parttime Software Engineering instructor at AASTU, Addis Ababa, Ethiopia. His research interests area includes Deep Learning, Machine Learning, Computer Vision, Big Data, and IoT.

Author Articles
Transfer Learning based Breast Cancer Classification via Deep Convolutional Neural Network

By Markos Wondim Walle Kula Kakeba Tune Natnael Tilahun Sinshaw Sudhir Kumar Mohapatra

DOI:, Pub. Date: 8 Aug. 2023

Breast cancer is a leading cause of death among women, and the subjectivity of human visual perception and lack of automated detection methods can lead to misclassification of breast cancer images. In this study, a breast cancer classification model using a Convolutional Neural Network (CNN) deep learning algorithm was proposed. The model demonstrated high accuracy in classifying breast images as benign or malignant, with a classification accuracy of 97.1%. The model was also able to run on low computational resources. The study used a dataset of 2009 breast images labeled by two radiologists and included six scenarios based on different hyperparameters, augmentation values, pretrained models, and models built from scratch. While the performance of the proposed model was promising, further improvement may be achieved by using a larger breast image dataset and a machine with more powerful GPU hardware.

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