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A Systematic Mapping Review of Image Annotation Studies for Obtaining Information Retrieval from Images

Yıl 2020, Cilt: 13 Sayı: 4, 423 - 434, 30.10.2020

Öz

Image annotation concept which aims to obtain and process image metadata from various kinds of images, to achieve meaningful results has become more and more critical in the information society in retrieving information from images. There are many approaches proposed in the literature, however, choosing the most appropriate ones is not an easy task. In this study, the key approaches on image annotation have been investigated through a systematic mapping with an extensive literature review. The novelty of our study is that it represents the first attempt to explore, investigate, map and analyze image annotation studies in literature and to help classify the studies, reveal research gaps, and prepare a visual summary for the research questions presented in this paper. The literature recommends the systematic mapping approach to investigate an area of interest from different perspectives. For this purpose, 95 studies were selected from a total of 404 studies identified. The examination of the literature on the domain shows that the available methods/techniques, tools, metrics, processes, or other technical approaches are not enough to produce a complete solution on their own. The necessity of generating new solutions by combining the proposed techniques and considering interdisciplinary approaches are also suggested.

Kaynakça

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Görüntülerden Bilgi Elde Etmek İçin Görüntü Açıklama Çalışmalarının Sistematik Haritalandırma İncelemesi

Yıl 2020, Cilt: 13 Sayı: 4, 423 - 434, 30.10.2020

Öz

Çeşitli görüntü türlerinden görüntü meta verilerini elde etmeyi, işlemeyi ve anlamlı sonuçlar çıkarmayı amaçlayan görüntü açıklaması kavramı, bilgi toplumunda görüntülerden bilgi edinme konusunda daha kritik hale gelmiştir. Bu konuda literatürde önerilen birçok yaklaşım vardır, ancak en uygun olanı seçmek kolay değildir. Bu çalışmada, görüntü açıklamalarındaki kilit yaklaşımlar, kapsamlı bir literatür taraması ve sistematik haritalama yoluyla incelenmiştir. Çalışmamızın yeniliği, literatürdeki görüntü açıklama çalışmalarını araştırmak, haritalamak ve analiz etmek ve seçilen çalışmaları sınıflandırmak, araştırma boşluklarını ortaya çıkarmak ve bu makalede sunulan araştırma soruları için görsel özet hazırlamak adına ilk denemeyi temsil etmesidir. Literatürde, ilgi alanını farklı açılardan araştırmak için sistematik haritalama yaklaşımı önerilmektedir. Bu amaçla, tespit edilen toplam 404 çalışma içerisinden 95 çalışma seçilmiştir. Alandaki literatürün incelenmesi, mevcut yöntemlerin / tekniklerin, araçların, metriklerin, süreçlerin veya diğer teknik yaklaşımların kendi başlarına eksiksiz bir çözüm üretmek için yeterli olmadığını göstermektedir. Önerilen teknikleri birleştirerek ve disiplinlerarası yaklaşımları dikkate alarak yeni çözümler üretmenin gerekliliği de önerilmiştir.

Kaynakça

  • V. Lavrenko, R. Manmatha, J. Jeon, “A Model for Learning the Semantics of Pictures”, Advances in Neural Information Processing Systems 17, Vancouver, Canada, 553-560, 13-18 December, 2004.
  • Internet: Halaschek, C. Wiener, Image Annotation on the Semantic Web, https://www.w3.org/2005/Incubator/mmsem/XGR-image-annotation/#annot_intro, 03.05.2019.
  • B. Kitchenham, S. Charters, Guidelines for Performing Systematic Literature Reviews in Software Engineering, Keele University, UK, 2007.
  • B. Kitchenham, et al., “Systematic literature reviews in software engineering – A systematic literature review”, Information and Software Technology, 51(1), 7-15, 2009.
  • K. Petersen, et al., “Systematic Mapping Studies in Software Engineering”, 12th International Conference on Evaluation and Assessment in Software Engineering, Bari, Italy, 68-77, 26-27 June, 2008.
  • J. Jill, L. Matheson, F. M. Lacey, Doing Your Literature Review: traditional and systematic techniques, SAGE Publishing, London, UK, 2011.
  • Internet: A. Sezen, Ç. Turhan, SM – Classification Scheme, https://drive.google.com/open?id=1cnItNure_P7oolIcoVmDqP5EXJMim00-HPOweH_qPDA, 10.10.2019.
  • X. Wang, et al., “High-level semantic image annotation based on hot Internet topics”, Multimedia Tools and Applications, 74(6), 2055-2084, 2015.
  • H. Bannour, C. Hudelot, “Building and using fuzzy multimedia ontologies for semantic image annotation”, Multimedia Tools and Applications, 72(3), 2107-2141, 2014.
  • A. Fakhari, A. M. E. Moghadam, “Combination of classification and regression in decision tree for multi-labeling image annotation and retrieval”, Applied Soft Computing, 13(2), 1292-1302, 2013.
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  • X. Li, et al., “A Locality Sensitive Low-Rank Model for Image Tag Completion”, IEEE Transactions on Multimedia, 18(3), 474-483, 2016.
  • D. A. Moreira, et al., “3D Markup of Radiological Images in ePAD, a Web-Based Image Annotation Tool”, IEEE 28th International Symposium on Computer-Based Medical Systems, Sao Carlos, Brazil, 97-102, 22-25 June, 2015.
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  • S. R. Kakade, N. R. Kakade, “A novel approach to link semantic gap between images and tags via probabilistic ranking”, IEEE International Conference on Computational Intelligence and Computing Research, Enathi, India, 1-6, 26-28 December, 2013.
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  • H-K. Hong, K-W. Park, D-H. Lee, “A Novel Semantic Tagging Technique Exploiting Wikipedia-Based Associated Words”, IEEE 39th Annual Computer Software and Applications Conference, Taichung, Taiwan, Vol. 3, 648-649, 1-5 July, 2015.
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  • J. Jing, et al., “Cognition-Based Semantic Annotation for Web Images”, Fourth International Conference on Big Data and Cloud Computing, Sydney, Australia, 540-546, 3-5 December, 2014.
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  • R. Socher, et al., “Grounded Compositional Semantics for Finding and Describing Images with Sentences”, Transactions of the Association for Computational Linguistics, 2(2014), 207-218, 2014.
  • G. Yunchao, et al., “A Multi-View Embedding Space for Modeling Internet Images, Tags, and Their Semantics”, International Journal of Computer Vision, 106(2), 210-233, 2014.
Toplam 120 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Bilgisayar Yazılımı
Bölüm Makaleler
Yazarlar

Arda Sezen

Çigdem Turhan 0000-0002-6595-7095

Yayımlanma Tarihi 30 Ekim 2020
Gönderilme Tarihi 24 Ekim 2019
Yayımlandığı Sayı Yıl 2020 Cilt: 13 Sayı: 4

Kaynak Göster

APA Sezen, A., & Turhan, Ç. (2020). A Systematic Mapping Review of Image Annotation Studies for Obtaining Information Retrieval from Images. Bilişim Teknolojileri Dergisi, 13(4), 423-434.