A complete human verified Turkish caption dataset for MS COCO and performance evaluation with well-known image caption models trained against it
Küçük Resim Yok
Tarih
2022
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
The procedure of generating natural language captions for an image is known as image captioning. Automatic image captioning is a particularly challenging task that stands at the junction of Computer Vision and Natural Language Processing. It has a variety of applications, including text-based image retrieval, assisting visually impaired users, and human-robot interaction. The majority of publications on the subject focus on the English language, which is an analytical language with characteristics differing from the agglutinative Turkish language. This work introduces the Turkish MS COCO dataset that extends the original MS COCO collection with captions in the Turkish language; experimental results surpass the current state-of-the-art for the Turkish image captioning field. Furthermore, the newly introduced database is also applicable for the study of machine translation. On the Turkish MS COCO dataset, the best performance has been achieved with the Meshed Memory Transformers with a Bleu-1 score of 0.72. The database is publicly available at https://github.com/BilgiAILAB/TurkishImageCaptioning. It is desired that the Turkish MS COCO dataset with the proposed benchmark will be an excellent resource for future studies on Turkish image captioning. © 2022 IEEE.
Açıklama
2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2022 -- 16 November 2022 through 18 November 2022 -- -- 185686
Anahtar Kelimeler
Cnn, Computer Vision, Deep Neural Networks, Lstm, Natural Language Processing, Rnn, Transformers, Turkish İmage Captioning, Turkish Ms Coco Database, Computer Vision, Database Systems, Human Robot İnteraction, Long Short-Term Memory, Natural Language Processing Systems, Petroleum Reservoir Evaluation, Image Captioning, Language Processing, Lstm, Natural Language Processing, Natural Languages, Rnn, Transformer, Turkish İmage Captioning, Turkish Ms Coco Database, Turkishs, Deep Neural Networks
Kaynak
International Conference on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2022
WoS Q Değeri
Scopus Q Değeri
N/A
