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Dergiler / Istanbul University Journal of Electrical and Electronics Engineering / 2002 / Cilt: 2 - Sayı: 2

Extraction of facial features using genetic cellular neural networks

Erdem BİLGİLİ
Ramazan ÇOBAN
Osman N. UÇAN
Sayfa
601–609
Yayın Tarihi
2022-10-18
DOI
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Yapay Zeka Hızlı Bakış & Çıkarımlar

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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

After the training process CNN templates are applied to various images.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:This paper presents proper CNN templates to locate face region consisting of eyes,eyebrows, nose and mouth in frontal face images.
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Temel Bulgular & Veri:At the begining, 72 random genes are selected.
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Sonuç & Katkı:After the training process CNN templates are applied to various images.
🔬Tür:Araştırma Makalesi
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Alan Parametreleri

Abstract

This paper presents proper CNN templates to locate face region consisting of eyes,eyebrows, nose and mouth in frontal face images. Training of CNN is done by using genetic algorithms. At the begining, 72 random genes are selected. Each gene includes binary codes of the elements of the CNN templates. CNN templates are designed as symmetric to satisfy the stability. After the training process CNN templates are applied to various images.

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Bu Makaleye Atıf Yap

BİLGİLİ, E., ÇOBAN, R., UÇAN, O. N. (2022). Extraction of facial features using genetic cellular neural networks. Istanbul University Journal of Electrical and Electronics Engineering, Cilt: 2 - Sayı: 2, 601–609. https://ajindex.com/articles/543948

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Kaynakça (1)

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