Identification and classification of objects in images obtained by UAV and orbital base imaging equipmenttion
To identify and classify objects on images obtained using UAV imaging and orbital-based imaging, a neural network classification model based on the use of an autoencoder and built on the architecture of an ensemble of multilayer perceptrons is proposed. Additionally, at the stage of highlighting inf...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Belarusian National Technical University
2023-02-01
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| Series: | Системный анализ и прикладная информатика |
| Subjects: | |
| Online Access: | https://sapi.bntu.by/jour/article/view/591 |
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| _version_ | 1849403936712163328 |
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| author | A. A. Doudkin V. V. Ganchenko A. V. Inyutin E. E. Marushko |
| author_facet | A. A. Doudkin V. V. Ganchenko A. V. Inyutin E. E. Marushko |
| author_sort | A. A. Doudkin |
| collection | DOAJ |
| description | To identify and classify objects on images obtained using UAV imaging and orbital-based imaging, a neural network classification model based on the use of an autoencoder and built on the architecture of an ensemble of multilayer perceptrons is proposed. Additionally, at the stage of highlighting informative features, is added a color information, which is based on the per-channel histograms and is invariant to the scale and rotations of the image. The model is implemented using the Keras library. The use of the proposed model for classification into four classes: “Fire”, “Smoke”, “Vegetation” and “Buildings”, allows to achieve a classification accuracy above 99%. |
| format | Article |
| id | doaj-art-cc58bac5418240b28ade47e81e4b1fae |
| institution | Kabale University |
| issn | 2309-4923 2414-0481 |
| language | English |
| publishDate | 2023-02-01 |
| publisher | Belarusian National Technical University |
| record_format | Article |
| series | Системный анализ и прикладная информатика |
| spelling | doaj-art-cc58bac5418240b28ade47e81e4b1fae2025-08-20T03:37:08ZengBelarusian National Technical UniversityСистемный анализ и прикладная информатика2309-49232414-04812023-02-0104303710.21122/2309-4923-2022-4-30-37440Identification and classification of objects in images obtained by UAV and orbital base imaging equipmenttionA. A. Doudkin0V. V. Ganchenko1A. V. Inyutin2E. E. Marushko3United Institute of Informatics Problems of the National Academy of Sciences of BelarusUnited Institute of Informatics Problems of the National Academy of Sciences of BelarusUnited Institute of Informatics Problems of the National Academy of Sciences of BelarusUnited Institute of Informatics Problems of the National Academy of Sciences of BelarusTo identify and classify objects on images obtained using UAV imaging and orbital-based imaging, a neural network classification model based on the use of an autoencoder and built on the architecture of an ensemble of multilayer perceptrons is proposed. Additionally, at the stage of highlighting informative features, is added a color information, which is based on the per-channel histograms and is invariant to the scale and rotations of the image. The model is implemented using the Keras library. The use of the proposed model for classification into four classes: “Fire”, “Smoke”, “Vegetation” and “Buildings”, allows to achieve a classification accuracy above 99%.https://sapi.bntu.by/jour/article/view/591metal fracturetexture featuresmacrogeometric descriptors |
| spellingShingle | A. A. Doudkin V. V. Ganchenko A. V. Inyutin E. E. Marushko Identification and classification of objects in images obtained by UAV and orbital base imaging equipmenttion Системный анализ и прикладная информатика metal fracture texture features macrogeometric descriptors |
| title | Identification and classification of objects in images obtained by UAV and orbital base imaging equipmenttion |
| title_full | Identification and classification of objects in images obtained by UAV and orbital base imaging equipmenttion |
| title_fullStr | Identification and classification of objects in images obtained by UAV and orbital base imaging equipmenttion |
| title_full_unstemmed | Identification and classification of objects in images obtained by UAV and orbital base imaging equipmenttion |
| title_short | Identification and classification of objects in images obtained by UAV and orbital base imaging equipmenttion |
| title_sort | identification and classification of objects in images obtained by uav and orbital base imaging equipmenttion |
| topic | metal fracture texture features macrogeometric descriptors |
| url | https://sapi.bntu.by/jour/article/view/591 |
| work_keys_str_mv | AT aadoudkin identificationandclassificationofobjectsinimagesobtainedbyuavandorbitalbaseimagingequipmenttion AT vvganchenko identificationandclassificationofobjectsinimagesobtainedbyuavandorbitalbaseimagingequipmenttion AT avinyutin identificationandclassificationofobjectsinimagesobtainedbyuavandorbitalbaseimagingequipmenttion AT eemarushko identificationandclassificationofobjectsinimagesobtainedbyuavandorbitalbaseimagingequipmenttion |