Deep Gabor Neural Network for Automatic Detection of Mine-Like Objects in Sonar Imagery
<p dir="ltr">With the advances in sonar imaging technology, sonar imagery has increasingly been used for oceanographic studies in civilian and military applications. High-resolution imaging sonars can be mounted on various survey platforms, typically autonomous underwater vehicles, w...
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| مؤلفون آخرون: | , , , , |
| منشور في: |
2020
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| _version_ | 1864513511906869248 |
|---|---|
| author | Hoang Thanh Le (18940666) |
| author2 | Son Lam Phung (18460602) Philip B. Chapple (18940669) Abdesselam Bouzerdoum (17900021) Christian H. Ritz (18940672) Le Chung Tran (18560944) |
| author2_role | author author author author author |
| author_facet | Hoang Thanh Le (18940666) Son Lam Phung (18460602) Philip B. Chapple (18940669) Abdesselam Bouzerdoum (17900021) Christian H. Ritz (18940672) Le Chung Tran (18560944) |
| author_role | author |
| dc.creator.none.fl_str_mv | Hoang Thanh Le (18940666) Son Lam Phung (18460602) Philip B. Chapple (18940669) Abdesselam Bouzerdoum (17900021) Christian H. Ritz (18940672) Le Chung Tran (18560944) |
| dc.date.none.fl_str_mv | 2020-05-18T12:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1109/access.2020.2995390 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Deep_Gabor_Neural_Network_for_Automatic_Detection_of_Mine-Like_Objects_in_Sonar_Imagery/26134090 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Engineering Maritime engineering Information and computing sciences Data management and data science Machine learning Gabor neural network detector Gabor layer side-scan sonar mine-like objects Feature extraction Sonar detection Detectors Neural networks Object detection Proposals |
| dc.title.none.fl_str_mv | Deep Gabor Neural Network for Automatic Detection of Mine-Like Objects in Sonar Imagery |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">With the advances in sonar imaging technology, sonar imagery has increasingly been used for oceanographic studies in civilian and military applications. High-resolution imaging sonars can be mounted on various survey platforms, typically autonomous underwater vehicles, which provide enhanced speed and improved data quality with long-range support. This paper addresses the automatic detection of mine-like objects using sonar images. The proposed Gabor-based detector is designed as a feature pyramid network with a small number of trainable weights. Our approach combines both semantically weak and strong features to handle mine-like objects at multiple scales effectively. For feature extraction, we introduce a parameterized Gabor layer which improves the generalization capability and computational efficiency. The steerable Gabor filtering modules are embedded within the cascaded layers to enhance the scale and orientation decomposition of images. The entire deep Gabor neural network is trained in an end-to-end manner from input sonar images with annotated mine-like objects. An extensive experimental evaluation on a real sonar dataset shows that the proposed method achieves competitive performance compared to the existing approaches.</p><h2>Other Information</h2><p dir="ltr">Published in: IEEE Access<br>License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2020.2995390" target="_blank">https://dx.doi.org/10.1109/access.2020.2995390</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_0144c55d2ac56660417d5cb8db051cac |
| identifier_str_mv | 10.1109/access.2020.2995390 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/26134090 |
| publishDate | 2020 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Deep Gabor Neural Network for Automatic Detection of Mine-Like Objects in Sonar ImageryHoang Thanh Le (18940666)Son Lam Phung (18460602)Philip B. Chapple (18940669)Abdesselam Bouzerdoum (17900021)Christian H. Ritz (18940672)Le Chung Tran (18560944)EngineeringMaritime engineeringInformation and computing sciencesData management and data scienceMachine learningGabor neural network detectorGabor layerside-scan sonarmine-like objectsFeature extractionSonar detectionDetectorsNeural networksObject detectionProposals<p dir="ltr">With the advances in sonar imaging technology, sonar imagery has increasingly been used for oceanographic studies in civilian and military applications. High-resolution imaging sonars can be mounted on various survey platforms, typically autonomous underwater vehicles, which provide enhanced speed and improved data quality with long-range support. This paper addresses the automatic detection of mine-like objects using sonar images. The proposed Gabor-based detector is designed as a feature pyramid network with a small number of trainable weights. Our approach combines both semantically weak and strong features to handle mine-like objects at multiple scales effectively. For feature extraction, we introduce a parameterized Gabor layer which improves the generalization capability and computational efficiency. The steerable Gabor filtering modules are embedded within the cascaded layers to enhance the scale and orientation decomposition of images. The entire deep Gabor neural network is trained in an end-to-end manner from input sonar images with annotated mine-like objects. An extensive experimental evaluation on a real sonar dataset shows that the proposed method achieves competitive performance compared to the existing approaches.</p><h2>Other Information</h2><p dir="ltr">Published in: IEEE Access<br>License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2020.2995390" target="_blank">https://dx.doi.org/10.1109/access.2020.2995390</a></p>2020-05-18T12:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1109/access.2020.2995390https://figshare.com/articles/journal_contribution/Deep_Gabor_Neural_Network_for_Automatic_Detection_of_Mine-Like_Objects_in_Sonar_Imagery/26134090CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/261340902020-05-18T12:00:00Z |
| spellingShingle | Deep Gabor Neural Network for Automatic Detection of Mine-Like Objects in Sonar Imagery Hoang Thanh Le (18940666) Engineering Maritime engineering Information and computing sciences Data management and data science Machine learning Gabor neural network detector Gabor layer side-scan sonar mine-like objects Feature extraction Sonar detection Detectors Neural networks Object detection Proposals |
| status_str | publishedVersion |
| title | Deep Gabor Neural Network for Automatic Detection of Mine-Like Objects in Sonar Imagery |
| title_full | Deep Gabor Neural Network for Automatic Detection of Mine-Like Objects in Sonar Imagery |
| title_fullStr | Deep Gabor Neural Network for Automatic Detection of Mine-Like Objects in Sonar Imagery |
| title_full_unstemmed | Deep Gabor Neural Network for Automatic Detection of Mine-Like Objects in Sonar Imagery |
| title_short | Deep Gabor Neural Network for Automatic Detection of Mine-Like Objects in Sonar Imagery |
| title_sort | Deep Gabor Neural Network for Automatic Detection of Mine-Like Objects in Sonar Imagery |
| topic | Engineering Maritime engineering Information and computing sciences Data management and data science Machine learning Gabor neural network detector Gabor layer side-scan sonar mine-like objects Feature extraction Sonar detection Detectors Neural networks Object detection Proposals |