Markos Wondim Walle

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



Research Interests:


Markos Wondim Walle earned a B.Sc. in Information Technology from Debre Markos University in Debre Markos, Ethiopia, in 2015, and an MSc in Software Engineering from Addis Ababa Science and Technology University in Addis Ababa, Ethiopia, in 2022. He worked as a software programmer at Addis Ababa Science and Technology University in Addis Ababa, Ethiopia, from 2016 to 2021. His research interests include big data analytics, machine learning, AI, and robotics, as well as software user acceptance testing and regression testing.

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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