most citedComparison of Deep Learning and Traditional Machine Learning Techniques for Classification of Pap Smear Images

14 citations · 20 across the 5 of their papers we have counts for

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5 papers

eess.IV20216 cited

Benchmarking of Lightweight Deep Learning Architectures for Skin Cancer Classification using ISIC 2017 Dataset

Abdurrahim Yilmaz, Mucahit Kalebasi, Yegor Samoylenko +2

Skin cancer is one of the deadly types of cancer and is common in the world. Recently, there has been a huge jump in the rate of people getting skin cancer. For this reason, the nu…

cs.RO2021

Mechatronic Investigation of Wound Healing Process by Using Micro Robot

Abdurrahim Yilmaz, Ali Anil Demircali, Serra Ozkasap +3

The purpose of this study is to find ideal forces for reducing cell stress in wound healing process by micro robots. Because of this aim, we made two simulations on COMSOL Multiphy…

physics.flu-dyn2021

The Effect of Pore Structure in Flapping Wings on Flight Performance

Abdurrahim Yilmaz, Asli Tekeci, Meryem Ece Ozyetkin +3

This study investigates the effects of porosity on flying creatures such as dragonflies, moths, hummingbirds, etc. wing and shows that pores can affect wing performance. These stud…

physics.bio-ph2021

Holographic Cell Stiffness Mapping Using Acoustic Stimulation

Rahmetullah Varol, Sevde Omeroglu, Zeynep Karavelioglu +8

Accurate assessment of stiffness distribution is essential due to the critical role of single cell mechanobiology in the regulation of many vital cellular processes such as prolife…

eess.IV202014 cited

Comparison of Deep Learning and Traditional Machine Learning Techniques for Classification of Pap Smear Images

Abdurrahim Yilmaz, Ali Anil Demircali, Sena Kocaman +1

A comprehensive study on machine and deep learning techniques for classification of normal and abnormal cervical cells by using pap smear images from Herlev dataset results are pre…