Deep Gated Recurrent Unit for Smartphone-Based Image Captioning

Volkan KILIÇ

doi:https://doi.org/10.35377/saucis.04.02.866409

Makale detayları

Deep Gated Recurrent Unit for Smartphone-Based Image Captioning

Yazarlar:

Volkan KILIÇ

Ana Başlıklar:

Özel bilgisayar yöntemleri

Dergi:

Sakarya University Journal of Computer and Information Sciences 2021 Vol.4 Issue 2, pp.181-191

Belge Tipi:

Makale

Yayın Tarihi:

8/2021

Belge Dili:

İngilizce

Document ID (Org No.):

2000551889

DOI:

https://doi.org/10.35377/saucis.04.02.866409

Özet:

 

Expressing the visual content of an image in natural language form has gained relevance due to technological and algorithmic advances together with improved computational processing capacity. Many smartphone applications for image captioning have been developed recently as built-in cameras provide advantages of easy-operation and portability, resulting in capturing an image whenever or wherever needed. Here, an encoder-decoder framework based new image captioning approach with a multi-layer gated recurrent unit is proposed. The Inception-v3 convolutional neural network is employed in the encoder due to its capability of more feature extraction from small regions. The proposed recurrent neural network-based decoder utilizes these features in the multi-layer gated recurrent unit to produce a natural language expression word-by-word. Experimental evaluations on the MSCOCO dataset demonstrate that our proposed approach has the advantage over existing approaches consistently across different evaluation metrics. With the integration of the proposed approach to our custom-designed Android application, named “VirtualEye+”, it has great potential to implement image captioning in daily routine.

Makale detayları

Deep Gated Recurrent Unit for Smartphone-Based Image Captioning

Yazarlar: Volkan KILIÇ

Ana Başlıklar: Özel bilgisayar yöntemleri

Dergi: Sakarya University Journal of Computer and Information Sciences 2021 Vol.4 Issue 2, pp.181-191

Belge Tipi: Makale

Yayın Tarihi: 8/2021

Belge Dili: İngilizce

Document ID (Org No.): 2000551889

DOI: https://doi.org/10.35377/saucis.04.02.866409

Sayı

Yazarlar:

Volkan KILIÇ

Ana Başlıklar:

Özel bilgisayar yöntemleri

Dergi:

Sakarya University Journal of Computer and Information Sciences 2021 Vol.4 Issue 2, pp.181-191

Belge Tipi:

Makale

Yayın Tarihi:

8/2021

Belge Dili:

İngilizce

Document ID (Org No.):

2000551889

DOI:

https://doi.org/10.35377/saucis.04.02.866409