Inspection of Underwater Hull Surface Condition Using the Soft Voting Ensemble of the Transfer-Learned Models
In this study, we propose a method for inspecting the condition of hull surfaces using underwater images acquired from the camera of a remotely controlled underwater vehicle (ROUV). To this end, a soft voting ensemble classifier comprising six well-known convolutional neural network models was used....
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-06-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/12/4392 |
| _version_ | 1827656759273062400 |
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| author | Byung Chul Kim Hoe Chang Kim Sungho Han Dong Kyou Park |
| author_facet | Byung Chul Kim Hoe Chang Kim Sungho Han Dong Kyou Park |
| author_sort | Byung Chul Kim |
| collection | DOAJ |
| description | In this study, we propose a method for inspecting the condition of hull surfaces using underwater images acquired from the camera of a remotely controlled underwater vehicle (ROUV). To this end, a soft voting ensemble classifier comprising six well-known convolutional neural network models was used. Using the transfer learning technique, the images of the hull surfaces were used to retrain the six models. The proposed method exhibited an accuracy of 98.13%, a precision of 98.73%, a recall of 97.50%, and an F<sub>1</sub>-score of 98.11% for the classification of the test set. Furthermore, the time taken for the classification of one image was verified to be approximately 56.25 ms, which is applicable to ROUVs that require real-time inspection. |
| first_indexed | 2024-03-09T22:33:51Z |
| format | Article |
| id | doaj.art-6a90c5b83cc042029f6604062abead68 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T22:33:51Z |
| publishDate | 2022-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-6a90c5b83cc042029f6604062abead682023-11-23T18:52:43ZengMDPI AGSensors1424-82202022-06-012212439210.3390/s22124392Inspection of Underwater Hull Surface Condition Using the Soft Voting Ensemble of the Transfer-Learned ModelsByung Chul Kim0Hoe Chang Kim1Sungho Han2Dong Kyou Park3School of Mechanical Engineering, Korea University of Technology and Education, Cheonan 31253, KoreaSchool of Mechanical Engineering, Korea University of Technology and Education, Cheonan 31253, KoreaSLM Global Co., Ltd., Daejeon 34037, KoreaDepartment of Electromechanical Convergence Engineering, Korea University of Technology and Education, Cheonan 31253, KoreaIn this study, we propose a method for inspecting the condition of hull surfaces using underwater images acquired from the camera of a remotely controlled underwater vehicle (ROUV). To this end, a soft voting ensemble classifier comprising six well-known convolutional neural network models was used. Using the transfer learning technique, the images of the hull surfaces were used to retrain the six models. The proposed method exhibited an accuracy of 98.13%, a precision of 98.73%, a recall of 97.50%, and an F<sub>1</sub>-score of 98.11% for the classification of the test set. Furthermore, the time taken for the classification of one image was verified to be approximately 56.25 ms, which is applicable to ROUVs that require real-time inspection.https://www.mdpi.com/1424-8220/22/12/4392hull cleaning conditionunderwater inspection imagesoft voting ensemble classificationtransfer learning |
| spellingShingle | Byung Chul Kim Hoe Chang Kim Sungho Han Dong Kyou Park Inspection of Underwater Hull Surface Condition Using the Soft Voting Ensemble of the Transfer-Learned Models Sensors hull cleaning condition underwater inspection image soft voting ensemble classification transfer learning |
| title | Inspection of Underwater Hull Surface Condition Using the Soft Voting Ensemble of the Transfer-Learned Models |
| title_full | Inspection of Underwater Hull Surface Condition Using the Soft Voting Ensemble of the Transfer-Learned Models |
| title_fullStr | Inspection of Underwater Hull Surface Condition Using the Soft Voting Ensemble of the Transfer-Learned Models |
| title_full_unstemmed | Inspection of Underwater Hull Surface Condition Using the Soft Voting Ensemble of the Transfer-Learned Models |
| title_short | Inspection of Underwater Hull Surface Condition Using the Soft Voting Ensemble of the Transfer-Learned Models |
| title_sort | inspection of underwater hull surface condition using the soft voting ensemble of the transfer learned models |
| topic | hull cleaning condition underwater inspection image soft voting ensemble classification transfer learning |
| url | https://www.mdpi.com/1424-8220/22/12/4392 |
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