Investigation of the efficiency of an interconnected convolutional neural network by classifying medical images

Lantang, Oktavian, Terdik, György, Hajdú, András, Tiba, Attila (2021) Investigation of the efficiency of an interconnected convolutional neural network by classifying medical images Annales Mathematicae et Informaticae (53.): Selected papers of the 1st Conference on Information Technology and Data Science. pp. 219-234. ISSN 1787-6117 (Online)

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Absztrakt (kivonat)

Convolutional Neural Network (CNN) for medical image classification has produced satisfying work [11, 12, 15]. Several pretrained models such as VGG19 [17], InceptionV3 [18], and MobileNet [8] are architectures that can be relied on to design high accuracy classification models. This work investigates the performance of three pretrained models with two methods of training. The first method trains the model independently, meaning that each model is given an input and trained separately, then the best results are determined by majority voting. In the second method the three pretrained models are trained simultaneously as interconnected models. The interconnected model adopts an ensemble architecture as is shown in [7]. By training multiple CNNs, this work gives optimum results compared to a single CNN. The difference is that the three subnetworks are trained simultaneously in an interconnected network and showing one expected result. In the training process the interconnected model determines each subnetwork’s weight by itself. Furthermore, this model will apply the most suitable weight to the final decision. The interconnected model showed comparable performance after training on several datasets. The measurement includes comparing the Accuracy, Precision and Recall scores as is shown in confusion matrix [3, 14].

Mű típusa:	Folyóiratcikk - Journal article
Szerző:	Szerző neve Email MTMT azonosító ORCID azonosító Közreműködés Lantang, Oktavian NEM RÉSZLETEZETT NEM RÉSZLETEZETT NEM RÉSZLETEZETT Szerző Terdik, György NEM RÉSZLETEZETT NEM RÉSZLETEZETT NEM RÉSZLETEZETT Szerző Hajdú, András NEM RÉSZLETEZETT NEM RÉSZLETEZETT NEM RÉSZLETEZETT Szerző Tiba, Attila NEM RÉSZLETEZETT NEM RÉSZLETEZETT NEM RÉSZLETEZETT Szerző
Megjegyzés:	This work was supported by the construction EFOP-3.6.3-VEKOP-16-2017-00002. The project was supported by the European Union, co-financed by the European Social Fund. Research was also supported by the ÚNKP-20-4-I New National Excellence Program of the Ministry for Innovation and Technology from the Source of the National Research, Development and Innovation Fund, and by LPDP Indonesia in the form of a doctoral scholarship (https://www.lpdp.kemenkeu.go.id).
Kapcsolódó URL-ek:	Befoglaló kötet
Kulcsszavak:	Convolutional Neural Network, medical image classification, interconnected model
Nyelv:	angol
DOI azonosító:	10.33039/ami.2021.04.001
ISSN:	1787-6117 (Online)
Felhasználó:	Tibor Gál
Dátum:	18 Máj 2021 16:28
Utolsó módosítás:	18 Máj 2021 16:28
URI:	http://publikacio.uni-eszterhazy.hu/id/eprint/7006

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