|
DDC
| 005.74 | |
Tác giả CN
| Nguyen, Minh Hai | |
Nhan đề
| A Method Of Semantic—Based Image Retrieval Using Graph Cut / Nguyen Minh Hai, Van The Thanh, Tran Van Lang | |
Tóm tắt
| Semantic extraction from images is a topical problem and is applied in many different semantic retrieval systems. In this paper, a method of image semantic retrieval is proposed based on a set of images similar to the input image. Since then, the semantics of the image are queried on the ontology by the visual word vector. The objects in each image are classified and features extracted based on Mask R—CNN, then stored on a graph cut to extract semantics from the image. For each image query, a similar set of images is retrieved on the graph cut and then a set of the visual words is extracted based on the classes obtained from Mask R—CNN, as the basis for querying semantics of an input image on ontology by SPARQL query. On the basis of the proposed method, an experiment was built and evaluated on the image datasets MIRFLICKR—QSK and MS COCO. | |
Từ khóa tự do
| Image retrieval | |
Từ khóa tự do
| Data mining | |
Từ khóa tự do
| Clustering | |
Từ khóa tự do
| Ontology | |
Tác giả(bs) CN
| Tran, Van Lang | |
Tác giả(bs) CN
| Van, The Thanh | |
Nguồn trích
| Tạp chí Tin học và Điều khiển học = Journal of Computer Science And Cybernetics 2022tr. 91-110
Số: 02 |
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| 00000nab#a2200000ui#4500 |
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| 001 | 52463 |
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| 002 | 9 |
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| 004 | 7253BEF3-F35A-47C1-AF55-67EA5F47D5E5 |
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| 005 | 202409271604 |
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| 008 | 081223s VN| vie |
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| 009 | 1 0 |
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| 039 | |y20240927160828|ztainguyendientu |
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| 040 | |aACTVN |
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| 041 | |avie |
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| 044 | |avm |
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| 082 | |a005.74 |
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| 100 | 10|aNguyen, Minh Hai |
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| 245 | |aA Method Of Semantic—Based Image Retrieval Using Graph Cut / |cNguyen Minh Hai, Van The Thanh, Tran Van Lang |
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| 520 | |aSemantic extraction from images is a topical problem and is applied in many different semantic retrieval systems. In this paper, a method of image semantic retrieval is proposed based on a set of images similar to the input image. Since then, the semantics of the image are queried on the ontology by the visual word vector. The objects in each image are classified and features extracted based on Mask R—CNN, then stored on a graph cut to extract semantics from the image. For each image query, a similar set of images is retrieved on the graph cut and then a set of the visual words is extracted based on the classes obtained from Mask R—CNN, as the basis for querying semantics of an input image on ontology by SPARQL query. On the basis of the proposed method, an experiment was built and evaluated on the image datasets MIRFLICKR—QSK and MS COCO. |
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| 653 | |aImage retrieval |
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| 653 | |aData mining |
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| 653 | |aClustering |
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| 653 | |aOntology |
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| 700 | |aTran, Van Lang |
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| 700 | |aVan, The Thanh |
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| 773 | 0 |tTạp chí Tin học và Điều khiển học = Journal of Computer Science And Cybernetics |d2022|gtr. 91-110|x1813-9663|i02 |
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| 890 | |a0|b0|c1|d0 |
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