TY - GEN
T1 - Evaluation of VGG-16 and VGG-19 Deep Learning Architecture for Classifying Dementia People
AU - Bagaskara, Abitya
AU - Suryanegara, Muhammad
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Dementia is a broad term that refers to a significant decline in one's ability to remember. Dementia is most commonly caused by Alzheimer's, which is often difficult to diagnose and late. In fact, the very mild stage of dementia is the most effective stage of diagnosis. Therefore, it will be a massive advantage if the diagnosis is successful at an early stage. This paper attempts to evaluate the VGG-16 and VGG-19 architecture by appending a fully connected layer at the network's end to identify four classes of dementia: very mild dementia, mild dementia, and moderate dementia, as well as a non-dementia or normal people control class. The results of this paper successfully detect with an accuracy of up to 99%. The highest accuracy value was recorded at 99.68% for training and 99.38% for validation. The analyses include the value components of the confusion matrix, i.e., precision, recall, and F1 Score.
AB - Dementia is a broad term that refers to a significant decline in one's ability to remember. Dementia is most commonly caused by Alzheimer's, which is often difficult to diagnose and late. In fact, the very mild stage of dementia is the most effective stage of diagnosis. Therefore, it will be a massive advantage if the diagnosis is successful at an early stage. This paper attempts to evaluate the VGG-16 and VGG-19 architecture by appending a fully connected layer at the network's end to identify four classes of dementia: very mild dementia, mild dementia, and moderate dementia, as well as a non-dementia or normal people control class. The results of this paper successfully detect with an accuracy of up to 99%. The highest accuracy value was recorded at 99.68% for training and 99.38% for validation. The analyses include the value components of the confusion matrix, i.e., precision, recall, and F1 Score.
KW - Alzheimer
KW - Artificial Intelligence
KW - CNN
KW - Deep learning
KW - Dementia
KW - VGG-16
KW - VGG-19
UR - http://www.scopus.com/inward/record.url?scp=85124281659&partnerID=8YFLogxK
U2 - 10.1109/IC2IE53219.2021.9649132
DO - 10.1109/IC2IE53219.2021.9649132
M3 - Conference contribution
AN - SCOPUS:85124281659
T3 - Proceedings - 2021 4th International Conference on Computer and Informatics Engineering: IT-Based Digital Industrial Innovation for the Welfare of Society, IC2IE 2021
SP - 1
EP - 4
BT - Proceedings - 2021 4th International Conference on Computer and Informatics Engineering
A2 - Ismail, Iklima Ermis
A2 - Hermawan, Indra
A2 - Rasyidin, Muhammad Yusuf Bagus
A2 - Huzaifa, Malisa
A2 - Muharram, Asep Taufik
A2 - Marcheeta, Noorlela
A2 - Kurniawati, Dewi
A2 - Yuly, Ade Rahma
A2 - Agustin, Maria
A2 - Nalawati, Rizki Elisa
A2 - Nugrahadi, Dodon Turianto
A2 - Budiman, Irwan
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th International Conference on Computer and Informatics Engineering, IC2IE 2021
Y2 - 14 September 2021
ER -