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2020 | OriginalPaper | Buchkapitel

Decision-Making Systems Based on Semantic Image Analysis

verfasst von : Natallia Iskra, Vitali Iskra, Marina Lukashevich

Erschienen in: Open Semantic Technologies for Intelligent System

Verlag: Springer International Publishing

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Abstract

In this paper principles of decision-making systems construction are considered. An approach to image analysis based on semantic model is proposed and studied. The results show an improvement in processing speed and image captioning quality based on Visual Genome dataset.

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Fußnoten
Literatur
1.
Zurück zum Zitat Agarwal, S., Terrail, J.O.D., Jurie, F.: Recent advances in object detection in the age of deep convolutional neural networks. arXiv preprint arXiv: 1809.03193 (2018) Agarwal, S., Terrail, J.O.D., Jurie, F.: Recent advances in object detection in the age of deep convolutional neural networks. arXiv preprint arXiv:​ 1809.​03193 (2018)
2.
Zurück zum Zitat Banerjee, S., Lavie, A.: METEOR: an automatic metric for MT evaluation with improved correlation with human judgments. In: Proceedings of the ACL Workshop on Intrinsic and Extrinsic Evaluation Measures for Machine Translation and/or Summarization, Ann Arbor, Michigan, pp. 65–72. Association for Computational Linguistics, June 2005. https://www.aclweb.org/anthology/W05-0909 Banerjee, S., Lavie, A.: METEOR: an automatic metric for MT evaluation with improved correlation with human judgments. In: Proceedings of the ACL Workshop on Intrinsic and Extrinsic Evaluation Measures for Machine Translation and/or Summarization, Ann Arbor, Michigan, pp. 65–72. Association for Computational Linguistics, June 2005. https://​www.​aclweb.​org/​anthology/​W05-0909
4.
Zurück zum Zitat Davydenko, I.: Semantic models, method and tools of knowledge bases coordinated development based on reusable components. In: Golenkov, V. (ed.) Open Semantic Technologies for Intelligent Systems, pp. 99–118. BSUIR, Minsk (2018) Davydenko, I.: Semantic models, method and tools of knowledge bases coordinated development based on reusable components. In: Golenkov, V. (ed.) Open Semantic Technologies for Intelligent Systems, pp. 99–118. BSUIR, Minsk (2018)
6.
Zurück zum Zitat Girshick, R., Donahue, J., Darrell, T., Malik, J.: Rich feature hierarchies for accurate object detection and semantic segmentation. In: 2014 IEEE Conference on Computer Vision and Pattern Recognition, pp. 580–587 (2014). https://doi.org/10.1109/CVPR.2014.81 Girshick, R., Donahue, J., Darrell, T., Malik, J.: Rich feature hierarchies for accurate object detection and semantic segmentation. In: 2014 IEEE Conference on Computer Vision and Pattern Recognition, pp. 580–587 (2014). https://​doi.​org/​10.​1109/​CVPR.​2014.​81
7.
Zurück zum Zitat Golenkov, V., Guliakina, N., Davydenko, I., Eremeev, A.: Methods and tools for ensuring compatibility of computer systems. In: Golenkov, V. (ed.) Otkrytye semanticheskie tekhnologii proektirovaniya intellektual’nykh system [Open semantic technologies for intelligent systems], pp. 25–52. BSUIR, Minsk (2019) Golenkov, V., Guliakina, N., Davydenko, I., Eremeev, A.: Methods and tools for ensuring compatibility of computer systems. In: Golenkov, V. (ed.) Otkrytye semanticheskie tekhnologii proektirovaniya intellektual’nykh system [Open semantic technologies for intelligent systems], pp. 25–52. BSUIR, Minsk (2019)
8.
Zurück zum Zitat Golovko, V., Kroshchanka, A., Ivashenko, V., Kovalev, M., Taberko, V., Ivaniuk, D.: Principles of decision-making systems building based on the integration of neural networks and semantic models. In: Golenkov, V. (ed.) Otkrytye semanticheskie tekhnologii proektirovaniya intellektual’nykh system [Open semantic technologies for intelligent systems], pp. 91–102. BSUIR, Minsk (2019) Golovko, V., Kroshchanka, A., Ivashenko, V., Kovalev, M., Taberko, V., Ivaniuk, D.: Principles of decision-making systems building based on the integration of neural networks and semantic models. In: Golenkov, V. (ed.) Otkrytye semanticheskie tekhnologii proektirovaniya intellektual’nykh system [Open semantic technologies for intelligent systems], pp. 91–102. BSUIR, Minsk (2019)
10.
Zurück zum Zitat Hursov, P.S., Iskra, N.A.: Algoritmy detektsii ob’ektov dlya analiza izobrazhenii [Object detection algorithms for image analysis]. In: Informatsionnye tekhnologii i sistemy: materialy mezhdunarodnoi nauchnoi konferentsii [Information Technologies and Systems: materials of the international scientific conference], pp. 128–129. Minsk (2019). (in Russian) Hursov, P.S., Iskra, N.A.: Algoritmy detektsii ob’ektov dlya analiza izobrazhenii [Object detection algorithms for image analysis]. In: Informatsionnye tekhnologii i sistemy: materialy mezhdunarodnoi nauchnoi konferentsii [Information Technologies and Systems: materials of the international scientific conference], pp. 128–129. Minsk (2019). (in Russian)
11.
Zurück zum Zitat Iskra, N., Iskra, V., Lukashevich, M.: Neural network based image understanding with ontological approach. In: Otkrytye semanticheskie tekhnologii proektirovaniya intellektual’nykh system: materialy mezhdunarodnoj nauchno-tekhnicheskoj konferencii [Open semantic technologies for intelligent systems: materials of the international scientific and technical conference], Minsk, pp. 113–122 (2019) Iskra, N., Iskra, V., Lukashevich, M.: Neural network based image understanding with ontological approach. In: Otkrytye semanticheskie tekhnologii proektirovaniya intellektual’nykh system: materialy mezhdunarodnoj nauchno-tekhnicheskoj konferencii [Open semantic technologies for intelligent systems: materials of the international scientific and technical conference], Minsk, pp. 113–122 (2019)
12.
Zurück zum Zitat Iskra, N.A., Mezhen’, A.L., Shunkevich, D.V.: Ontologiya predmetnoj oblasti prostranstvennyh sushchnostej dlya sistemy semanticheskogo analiza izobrazhenij [Ontology of the subject area of spatial entities for the system of semantic image analysis]. In: Informatsionnye tekhnologii i sistemy: materialy mezhdunarodnoi nauchnoi konferentsii [Information Technologies and Systems: of the international scientific conference], Minsk, pp. 112–113 (2019). (in Russian) Iskra, N.A., Mezhen’, A.L., Shunkevich, D.V.: Ontologiya predmetnoj oblasti prostranstvennyh sushchnostej dlya sistemy semanticheskogo analiza izobrazhenij [Ontology of the subject area of spatial entities for the system of semantic image analysis]. In: Informatsionnye tekhnologii i sistemy: materialy mezhdunarodnoi nauchnoi konferentsii [Information Technologies and Systems: of the international scientific conference], Minsk, pp. 112–113 (2019). (in Russian)
17.
Zurück zum Zitat Miller, G.A.: WordNet: An Electronic Lexical Database. MIT Press, Cambridge (1998)MATH Miller, G.A.: WordNet: An Electronic Lexical Database. MIT Press, Cambridge (1998)MATH
20.
Zurück zum Zitat Shunkevich, D.: Agent-oriented models, method and tools of compatible problem solvers development for intelligent systems. In: Golenkov, V. (ed.) Open Semantic Technologies for Intelligent Systems, pp. 119–132. BSUIR, Minsk (2018) Shunkevich, D.: Agent-oriented models, method and tools of compatible problem solvers development for intelligent systems. In: Golenkov, V. (ed.) Open Semantic Technologies for Intelligent Systems, pp. 119–132. BSUIR, Minsk (2018)
Metadaten
Titel
Decision-Making Systems Based on Semantic Image Analysis
verfasst von
Natallia Iskra
Vitali Iskra
Marina Lukashevich
Copyright-Jahr
2020
DOI
https://doi.org/10.1007/978-3-030-60447-9_7

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