Inception-ResNet-v2 with Leakyrelu and Averagepooling for More Reliable and Accurate Classification of Chest X-ray Images

2020 Medical Technologies Congress (TIPTEKNO), Antalya, Türkiye, 19 - 20 Kasım 2020

Pneumonia is one of the most commonly seen

illnesses in the world and its diagnosis needs some expertise.

Computer aided diagnosis methods are used extensively in a lot of

fields like health care. This study uses Inception-ResNet-v2 deep

learning architecture. Classification is done by using this

architecture. ReLU activation function seen in network

architecture is changed with LeakyReLU activation function and

classification task is done. After that, all of the maxpooling layers

seen in network architecture is changed with avepooling layers

and again classification task is done. Lastly, this seperate changes

done in network architecture is combined in one network and

again classification task is done with new network architecture.

Four experiments are done in total and their results are compared.

The best case with a sensitivity value of 93.16% and with a

specificity value of 93.59% is obtained in Inception Resnet V2 with

together application of LeakyReLU and Averagepooling.