Aggregated Context Network For Semantic Segmentation Of Aerial Images
With the considerable advancement of remote sensing technology and computer vision, automatic scene understanding for very high-resolution aerial (VHR) imagery became a necessary research topic. Semantic segmentation of VHR imagery is an important task where context information plays a crucial role....
Gespeichert in:
| Veröffentlicht in: | Proceedings - International Conference on Image Processing S. 1526 - 1530 |
|---|---|
| Hauptverfasser: | , , |
| Format: | Tagungsbericht |
| Sprache: | Englisch |
| Veröffentlicht: |
IEEE
16.10.2022
|
| Schlagworte: | |
| ISSN: | 2381-8549 |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| Abstract | With the considerable advancement of remote sensing technology and computer vision, automatic scene understanding for very high-resolution aerial (VHR) imagery became a necessary research topic. Semantic segmentation of VHR imagery is an important task where context information plays a crucial role. Adequate feature delineation is difficult due to high-class imbalance in remotely sensed data. In this work, we proposed a variant of encoder-decoder-based architecture where residual attentive skip connections are incorporated. We added a multi-context block in each of the encoder units to capture multi-scale and multi-context features and used dense connections for effective feature extraction. A comprehensive set of experiments reveal that the proposed scheme outperformed recently published work by 3% in overall accuracy and F1 score for ISPRS Vaihingen and ISPRS Potsdam benchmark datasets. |
|---|---|
| AbstractList | With the considerable advancement of remote sensing technology and computer vision, automatic scene understanding for very high-resolution aerial (VHR) imagery became a necessary research topic. Semantic segmentation of VHR imagery is an important task where context information plays a crucial role. Adequate feature delineation is difficult due to high-class imbalance in remotely sensed data. In this work, we proposed a variant of encoder-decoder-based architecture where residual attentive skip connections are incorporated. We added a multi-context block in each of the encoder units to capture multi-scale and multi-context features and used dense connections for effective feature extraction. A comprehensive set of experiments reveal that the proposed scheme outperformed recently published work by 3% in overall accuracy and F1 score for ISPRS Vaihingen and ISPRS Potsdam benchmark datasets. |
| Author | Chutia, Dibyajyoti Chouhan, Avinash Sur, Arijit |
| Author_xml | – sequence: 1 givenname: Avinash surname: Chouhan fullname: Chouhan, Avinash organization: North Eastern Space Applications Centre,Umiam,Meghalaya,India,793103 – sequence: 2 givenname: Arijit surname: Sur fullname: Sur, Arijit organization: Indian Institute of Technology,Guwahati,Assam,India,781039 – sequence: 3 givenname: Dibyajyoti surname: Chutia fullname: Chutia, Dibyajyoti organization: North Eastern Space Applications Centre,Umiam,Meghalaya,India,793103 |
| BookMark | eNotj9FKwzAYRqMouE6fQJC8QOufpE2Ty1G2WRhOUK9Hkv4p0bWVNKC-vQN39Z1zc-DLyNU4jUjIA4OCMdCPbdO-lLKqZcGB80IrrYDJC5IxKatSSw71JVlwoViuTn5Dsnn-AODABFuQ9arvI_YmYUebaUz4k-gzpu8pftLNFOkrDmZMwZ2gH3BMJoVppHtPVxiDOdJ2MD3Ot-Tam-OMd-ddkvfN-q15ynf7bdusdnngIFJuvOm8s1qVyrjKaonaee2k78CBBWmEAKO5lQqVrz1YFLqsO22xVqzSXizJ_X83IOLhK4bBxN_D-bL4Aw0dTkA |
| ContentType | Conference Proceeding |
| DBID | 6IE 6IH CBEJK RIE RIO |
| DOI | 10.1109/ICIP46576.2022.9898016 |
| DatabaseName | IEEE Electronic Library (IEL) Conference Proceedings IEEE Proceedings Order Plan (POP) 1998-present by volume IEEE Xplore All Conference Proceedings IEEE Electronic Library (IEL) IEEE Proceedings Order Plans (POP) 1998-present |
| DatabaseTitleList | |
| Database_xml | – sequence: 1 dbid: RIE name: IEEE Electronic Library (IEL) url: https://ieeexplore.ieee.org/ sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Applied Sciences |
| EISBN | 1665496207 9781665496209 |
| EISSN | 2381-8549 |
| EndPage | 1530 |
| ExternalDocumentID | 9898016 |
| Genre | orig-research |
| GroupedDBID | 6IE 6IF 6IH 6IK 6IL 6IM 6IN AAJGR AAWTH ADZIZ ALMA_UNASSIGNED_HOLDINGS BEFXN BFFAM BGNUA BKEBE BPEOZ CBEJK CHZPO IPLJI M43 OCL RIE RIL RIO RNS |
| ID | FETCH-LOGICAL-i203t-afadfcb9848ac5b96e9cf9c6fd0c0b06a330a92b68e8f7f0be3947d9be78159f3 |
| IEDL.DBID | RIE |
| ISICitedReferencesCount | 2 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001058109501123&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| IngestDate | Wed Aug 27 02:19:00 EDT 2025 |
| IsPeerReviewed | false |
| IsScholarly | true |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-i203t-afadfcb9848ac5b96e9cf9c6fd0c0b06a330a92b68e8f7f0be3947d9be78159f3 |
| PageCount | 5 |
| ParticipantIDs | ieee_primary_9898016 |
| PublicationCentury | 2000 |
| PublicationDate | 2022-Oct.-16 |
| PublicationDateYYYYMMDD | 2022-10-16 |
| PublicationDate_xml | – month: 10 year: 2022 text: 2022-Oct.-16 day: 16 |
| PublicationDecade | 2020 |
| PublicationTitle | Proceedings - International Conference on Image Processing |
| PublicationTitleAbbrev | ICIP |
| PublicationYear | 2022 |
| Publisher | IEEE |
| Publisher_xml | – name: IEEE |
| SSID | ssj0020131 |
| Score | 2.219387 |
| Snippet | With the considerable advancement of remote sensing technology and computer vision, automatic scene understanding for very high-resolution aerial (VHR) imagery... |
| SourceID | ieee |
| SourceType | Publisher |
| StartPage | 1526 |
| SubjectTerms | Benchmark testing Computer architecture Computer vision Convolution Feature extraction multi-context block residual attentive connection Semantic segmentation Semantics Task analysis |
| Title | Aggregated Context Network For Semantic Segmentation Of Aerial Images |
| URI | https://ieeexplore.ieee.org/document/9898016 |
| WOSCitedRecordID | wos001058109501123&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LawIxEB5UeujJtlr6Joceu5p95XEUUSoUK_SBN9kkE_GgFl1Lf36TuFgKvfQ2BEJgksx8M8k3A3DPc4YOiORRlvlsFcosknmuoiIxaWw51UmoU_D-xMdjMZ3KSQ0eDlwYRAyfz7DjxfCWb9Z651NlXd_r0EGUOtQ5Z3uu1iG48nVjKgZwTGV31B9NMubAtAsBk6RTzfzVQiV4kGHzf2ufQPuHikcmBydzCjVcnUGzwo6kupnbFgx6cxc5-5yYIaHi1FdJxvsv3mS43pAXXDodLrQT5suKb7Qiz5b0whEko6UzLNs2vA0Hr_3HqGqREC0SmpZRYQtjtZIiE4XOlWQotZWaWUM1VZQVaUoLmSgmUFhuqcJUZtxIhVw4IGPTc2is1iu8AKI5NSGCEFplNqdFrEyCuaapMVpScQktr5XZx74KxqxSyNXfw9dw7BXvrXzMbqBRbnZ4C0f6s1xsN3dh674B2deafw |
| linkProvider | IEEE |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LTwIxEG4QTfSEisa3PXh0odttd9sjIRA24koiGm5k-yIcWAwsxp9vWzYYEy_emiZNk5l25ptpvxkAHhIaawtEaECIy1ZpTgJOqQhyrKLQJEhiX6fgfZhkGZtM-KgGHndcGK21_3ymW27o3_LVUm5cqqzteh1aiLIH9ikhGG3ZWrvwylWOqTjAIeLttJuOSGzhtA0CMW5Va381UfE-pN_43-7H4OyHjAdHOzdzAmq6OAWNCj3C6m6um6DXmdnY2WXFFPQ1p75KmG0_ecP-cgVf9cJKcS7tYLaoGEcFfDGw4w8hTBfWtKzPwFu_N-4OgqpJQjDHKCqD3OTKSMEZYbmkgseaS8NlbBSSSKA4jyKUcyxipplJDBI64iRRXOiEWShjonNQL5aFvgBQJkj5GIJJQQxFeSgU1lSiSCnJEbsETSeV6ce2Dsa0EsjV39P34HAwfh5Oh2n2dA2OnBKczQ_jG1AvVxt9Cw7kZzlfr-68Gr8BEcWdxg |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=proceeding&rft.title=Proceedings+-+International+Conference+on+Image+Processing&rft.atitle=Aggregated+Context+Network+For+Semantic+Segmentation+Of+Aerial+Images&rft.au=Chouhan%2C+Avinash&rft.au=Sur%2C+Arijit&rft.au=Chutia%2C+Dibyajyoti&rft.date=2022-10-16&rft.pub=IEEE&rft.eissn=2381-8549&rft.spage=1526&rft.epage=1530&rft_id=info:doi/10.1109%2FICIP46576.2022.9898016&rft.externalDocID=9898016 |