{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T22:29:38Z","timestamp":1780439378305,"version":"3.54.1"},"reference-count":69,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100003471","name":"Harbin Engineering University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003471","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Digital Signal Processing"],"published-print":{"date-parts":[[2026,6]]},"DOI":"10.1016\/j.dsp.2026.106033","type":"journal-article","created":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T00:19:59Z","timestamp":1772583599000},"page":"106033","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"special_numbering":"C","title":["UCOE-DETR: An accurate detection transformer with underwater characteristic-oriented encoder"],"prefix":"10.1016","volume":"176","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-0919-1847","authenticated-orcid":false,"given":"Jianhua","family":"Li","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1596-0309","authenticated-orcid":false,"given":"Liying","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"2","key":"10.1016\/j.dsp.2026.106033_bib0001","doi-asserted-by":"crossref","first-page":"1726","DOI":"10.1109\/TVT.2023.3318629","article-title":"Intelligent underwater object detection and image restoration for autonomous underwater vehicles","volume":"73","author":"Fayaz","year":"2023","journal-title":"IEEE Trans. Veh. Technol."},{"key":"10.1016\/j.dsp.2026.106033_bib0002","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2021.115306","article-title":"S-FPN: A shortcut feature pyramid network for sea cucumber detection in underwater images","volume":"182","author":"Peng","year":"2021","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.dsp.2026.106033_bib0003","doi-asserted-by":"crossref","DOI":"10.1016\/j.ecoinf.2024.102680","article-title":"Real-time underwater object detection technology for complex underwater environments based on deep learning","author":"Zhou","year":"2024","journal-title":"Ecol. Inform."},{"key":"10.1016\/j.dsp.2026.106033_bib0004","series-title":"OCEANS 2017-Aberdeen","first-page":"1","article-title":"Vision based real-time fish detection using convolutional neural network","author":"Sung","year":"2017"},{"issue":"6","key":"10.1016\/j.dsp.2026.106033_bib0005","doi-asserted-by":"crossref","first-page":"793","DOI":"10.1007\/s42979-024-03170-z","article-title":"Enhancing underwater object detection: leveraging YOLOv8m for improved subaquatic monitoring","volume":"5","author":"Bajpai","year":"2024","journal-title":"SN Comput. Sci."},{"issue":"7","key":"10.1016\/j.dsp.2026.106033_bib0006","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s10462-024-10788-1","article-title":"Dynamic YOLO for small underwater object detection","volume":"57","author":"Chen","year":"2024","journal-title":"Artif. Intell. Rev."},{"key":"10.1016\/j.dsp.2026.106033_bib0007","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2023.107766","article-title":"Weighted multi-error information entropy based you only look once network for underwater object detection","volume":"130","author":"Ma","year":"2024","journal-title":"Eng. Appl. Artif. Intell."},{"key":"10.1016\/j.dsp.2026.106033_bib0008","series-title":"2022 19th International Bhurban Conference on Applied Sciences and Technology (IBCAST)","first-page":"951","article-title":"Marine object detection using transformers","author":"Ali","year":"2022"},{"issue":"2","key":"10.1016\/j.dsp.2026.106033_bib0009","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0298739","article-title":"Underwater object detection method based on learnable query recall mechanism and lightweight adapter","volume":"19","author":"Lin","year":"2024","journal-title":"PLoS One"},{"issue":"7","key":"10.1016\/j.dsp.2026.106033_bib0010","doi-asserted-by":"crossref","first-page":"4996","DOI":"10.1109\/TPAMI.2025.3548652","article-title":"Spatial residual for underwater object detection","volume":"47","author":"Zhou","year":"2025","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.dsp.2026.106033_bib0011","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"13619","article-title":"Dn-detr: accelerate detr training by introducing query denoising","author":"Li","year":"2022"},{"key":"10.1016\/j.dsp.2026.106033_bib0012","article-title":"U-Decn: end-to-end underwater object detection convnet with improved denoising training","volume":"63","author":"Liu","year":"2025","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.dsp.2026.106033_bib0013","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","first-page":"17425","article-title":"Swiftformer: efficient additive attention for transformer-based real-time mobile vision applications","author":"Shaker","year":"2023"},{"issue":"22","key":"10.1016\/j.dsp.2026.106033_bib0014","doi-asserted-by":"crossref","first-page":"4265","DOI":"10.3390\/rs16224265","article-title":"Small object detection in uav remote sensing images based on intra-group multi-scale fusion attention and adaptive weighted feature fusion mechanism","volume":"16","author":"Yuan","year":"2024","journal-title":"Remote Sens."},{"key":"10.1016\/j.dsp.2026.106033_bib0015","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2024.111111","article-title":"Weakly supervised underwater object real-time detection based on high-resolution attention class activation mapping and category hierarchy","volume":"159","author":"Hua","year":"2025","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.dsp.2026.106033_bib0016","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"16965","article-title":"Detrs beat yolos on real-time object detection","author":"Zhao","year":"2024"},{"key":"10.1016\/j.dsp.2026.106033_bib0017","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2023.110222","article-title":"A gated cross-domain collaborative network for underwater object detection","volume":"149","author":"Dai","year":"2024","journal-title":"Pattern Recognit."},{"issue":"7","key":"10.1016\/j.dsp.2026.106033_bib0018","doi-asserted-by":"crossref","first-page":"9215","DOI":"10.1109\/TII.2024.3383537","article-title":"A novel underwater detection method for ambiguous object finding via distraction mining","volume":"20","author":"Yuan","year":"2024","journal-title":"IEEE Trans. Ind. Inf."},{"key":"10.1016\/j.dsp.2026.106033_bib0019","series-title":"European Conference on Computer Vision","first-page":"239","article-title":"Context-guided spatial feature reconstruction for efficient semantic segmentation","author":"Ni","year":"2024"},{"key":"10.1016\/j.dsp.2026.106033_bib0020","series-title":"European Conference on Computer Vision","first-page":"343","article-title":"Frequency-spatial entanglement learning for camouflaged object detection","author":"Sun","year":"2024"},{"key":"10.1016\/j.dsp.2026.106033_bib0021","article-title":"SFUDNet: Underwater object detection via spatail-frequency domain modulation with mixture of experts","author":"Xu","year":"2025","journal-title":"Knowl. Based Syst."},{"key":"10.1016\/j.dsp.2026.106033_bib0022","series-title":"2025 IEEE International Conference on Multimedia and Expo (ICME)","first-page":"1","article-title":"Rethinking denoising training for DETR-based object detection","author":"Jiang","year":"2025"},{"issue":"2","key":"10.1016\/j.dsp.2026.106033_bib0023","doi-asserted-by":"crossref","first-page":"287","DOI":"10.3390\/math13020287","article-title":"FSDN-DETR: Enhancing fuzzy systems adapter with denoising anchor boxes for transfer learning in small object detection","volume":"13","author":"Li","year":"2025","journal-title":"Mathematics"},{"issue":"6","key":"10.1016\/j.dsp.2026.106033_bib0024","doi-asserted-by":"crossref","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","article-title":"Faster R-CNN: towards real-time object detection with region proposal networks","volume":"39","author":"Ren","year":"2016","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.dsp.2026.106033_bib0025","unstructured":"J. Hong, M. Fulton, J. Sattar, Trashcan: A semantically-segmented dataset towards visual detection of marine debris, arXiv: 2007.08097(2020). 10.48550\/arXiv.2007.08097."},{"key":"10.1016\/j.dsp.2026.106033_bib0026","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"7464","article-title":"YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors","author":"Wang","year":"2023"},{"key":"10.1016\/j.dsp.2026.106033_bib0027","unstructured":"G. Jocher, Yolov8, 2023, https:\/\/github.com\/ultralytics\/ultralytics\/tree\/main."},{"key":"10.1016\/j.dsp.2026.106033_bib0028","series-title":"European Conference on Computer Vision","first-page":"1","article-title":"Yolov9: learning what you want to learn using programmable gradient information","author":"Wang","year":"2024"},{"key":"10.1016\/j.dsp.2026.106033_bib0029","series-title":"European Conference on Computer Vision","first-page":"213","article-title":"End-to-end object detection with transformers","author":"Carion","year":"2020"},{"key":"10.1016\/j.dsp.2026.106033_bib0030","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","first-page":"3651","article-title":"Conditional detr for fast training convergence","author":"Meng","year":"2021"},{"key":"10.1016\/j.dsp.2026.106033_bib0031","unstructured":"X. Zhu, W. Su, L. Lu, B. Li, X. Wang, J. Dai, Deformable detr: Deformable transformers for end-to-end object detection, arXiv: 2010.04159(2020). 10.48550\/arXiv.2010.04159."},{"key":"10.1016\/j.dsp.2026.106033_bib0032","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"17027","article-title":"Ms-detr: efficient detr training with mixed supervision","author":"Zhao","year":"2024"},{"issue":"5","key":"10.1016\/j.dsp.2026.106033_bib0033","doi-asserted-by":"crossref","first-page":"2831","DOI":"10.1109\/TCSVT.2021.3100059","article-title":"A new dataset, poisson GAN and aquanet for underwater object grabbing","volume":"32","author":"Liu","year":"2021","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.dsp.2026.106033_bib0034","doi-asserted-by":"crossref","DOI":"10.1016\/j.cviu.2024.104225","article-title":"Scene-cGAN: a GAN for underwater restoration and scene depth estimation","volume":"250","author":"Gonz\u00e1lez-Sabbagh","year":"2025","journal-title":"Comput. Vision Image Understanding"},{"key":"10.1016\/j.dsp.2026.106033_bib0035","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2025.111677","article-title":"Detail-focused and polarization-guided multi-modality fusion for underwater image clarity enhancing","volume":"159","author":"Yao","year":"2025","journal-title":"Eng. Appl. Artif. Intell."},{"key":"10.1016\/j.dsp.2026.106033_bib0036","article-title":"A lightweight polarization-Guided plug-in for underwater image enhancement","author":"Ju","year":"2025","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.dsp.2026.106033_bib0037","series-title":"ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","first-page":"2588","article-title":"Roimix: proposal-fusion among multiple images for underwater object detection","author":"Lin","year":"2020"},{"issue":"11","key":"10.1016\/j.dsp.2026.106033_bib0038","doi-asserted-by":"crossref","first-page":"6887","DOI":"10.1109\/TCSVT.2023.3271644","article-title":"Learning heavily-degraded prior for underwater object detection","volume":"33","author":"Fu","year":"2023","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"issue":"5","key":"10.1016\/j.dsp.2026.106033_bib0039","doi-asserted-by":"crossref","first-page":"1078","DOI":"10.1049\/cit2.12325","article-title":"Edge-guided representation learning for underwater object detection","volume":"9","author":"Dai","year":"2024","journal-title":"CAAI Trans. Intell. Technol."},{"key":"10.1016\/j.dsp.2026.106033_bib0040","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2024.111672","article-title":"A dual-branch joint learning network for underwater object detection","volume":"293","author":"Wang","year":"2024","journal-title":"Knowl. Based Syst."},{"key":"10.1016\/j.dsp.2026.106033_bib0041","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2023.109511","article-title":"Underwater object detection algorithm based on feature enhancement and progressive dynamic aggregation strategy","volume":"139","author":"Hua","year":"2023","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.dsp.2026.106033_bib0042","series-title":"ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","first-page":"2715","article-title":"SRP-UOD: Multi-Branch hybrid network framework based on structural re-Parameterization for underwater small object detection","author":"Shi","year":"2024"},{"issue":"5","key":"10.1016\/j.dsp.2026.106033_bib0043","doi-asserted-by":"crossref","first-page":"7183","DOI":"10.1007\/s40747-024-01533-w","article-title":"Reparameterized underwater object detection network improved by cone-rod cell module and WIOU loss","volume":"10","author":"Yang","year":"2024","journal-title":"Complex Intell. Syst."},{"key":"10.1016\/j.dsp.2026.106033_bib0044","article-title":"SU-YOLO: Spiking neural network for efficient underwater object detection","author":"Li","year":"2025","journal-title":"Neurocomputing"},{"key":"10.1016\/j.dsp.2026.106033_bib0045","series-title":"2023 IEEE International Conference on Real-time Computing and Robotics (RCAR)","first-page":"762","article-title":"Underwater object detection based on dn-detr","author":"Mai","year":"2023"},{"issue":"6","key":"10.1016\/j.dsp.2026.106033_bib0046","doi-asserted-by":"crossref","first-page":"864","DOI":"10.3390\/jmse12060864","article-title":"Dyfish-DETR: underwater fish image recognition based on detection transformer","volume":"12","author":"Wang","year":"2024","journal-title":"J. Mar. Sci. Eng."},{"key":"10.1016\/j.dsp.2026.106033_bib0047","first-page":"1","article-title":"Lightweight LUW-DETR for efficient underwater benthic organism detection","author":"Li","year":"2025","journal-title":"Vis. Comput."},{"key":"10.1016\/j.dsp.2026.106033_bib0048","doi-asserted-by":"crossref","DOI":"10.1016\/j.marpolbul.2025.118537","article-title":"Lightweight underwater debris detection model based on improved RT-DETR","volume":"222","author":"Lin","year":"2026","journal-title":"Mar. Pollut. Bull."},{"key":"10.1016\/j.dsp.2026.106033_bib0049","unstructured":"H. Zhang, F. Li, S. Liu, L. Zhang, H. Su, J. Zhu, L.M. Ni, H.-Y. Shum, Dino: Detr with improved denoising anchor boxes for end-to-end object detection, arXiv: 2203.03605(2022). 10.48550\/arXiv.2203.03605."},{"key":"10.1016\/j.dsp.2026.106033_bib0050","article-title":"Unsupervised lifelong person re-identification via affinity harmonization","author":"Tan","year":"2025","journal-title":"ACM Trans. Multimedia Comput., Commun. Appl."},{"key":"10.1016\/j.dsp.2026.106033_bib0051","doi-asserted-by":"crossref","first-page":"9385","DOI":"10.1109\/TMM.2025.3613125","article-title":"Tensor completion framework by graph refinement for incomplete multi-view clustering","volume":"27","author":"Wang","year":"2025","journal-title":"IEEE Trans. Multimedia"},{"key":"10.1016\/j.dsp.2026.106033_bib0052","doi-asserted-by":"crossref","DOI":"10.1109\/TCSVT.2025.3647673","article-title":"Hierarchical sequential context modelling for high-Fidelity image inpainting","author":"Sun","year":"2025","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.dsp.2026.106033_bib0053","doi-asserted-by":"crossref","first-page":"875","DOI":"10.1016\/j.patcog.2016.06.013","article-title":"Dual autoencoders features for imbalance classification problem","volume":"60","author":"Ng","year":"2016","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.dsp.2026.106033_bib0054","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"6980","article-title":"C2am Loss: chasing a better decision boundary for long-tail object detection","author":"Wang","year":"2022"},{"key":"10.1016\/j.dsp.2026.106033_bib0055","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"821","article-title":"Libra r-cnn: towards balanced learning for object detection","author":"Pang","year":"2019"},{"issue":"3","key":"10.1016\/j.dsp.2026.106033_bib0056","doi-asserted-by":"crossref","first-page":"2452","DOI":"10.1109\/TETCI.2024.3462249","article-title":"Bauodnet for class imbalance learning in underwater object detection","volume":"9","author":"Chen","year":"2024","journal-title":"IEEE Trans. Emerg. Top. Comput. Intell."},{"key":"10.1016\/j.dsp.2026.106033_bib0057","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2024.110649","article-title":"Underwater object detection in noisy imbalanced datasets","volume":"155","author":"Chen","year":"2024","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.dsp.2026.106033_bib0058","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","first-page":"770","article-title":"Deep residual learning for image recognition","author":"He","year":"2016"},{"issue":"4","key":"10.1016\/j.dsp.2026.106033_bib0059","doi-asserted-by":"crossref","first-page":"3279","DOI":"10.1109\/TKDE.2021.3126456","article-title":"A general survey on attention mechanisms in deep learning","volume":"35","author":"Brauwers","year":"2021","journal-title":"IEEE Trans. Knowl. Data Eng."},{"issue":"1","key":"10.1016\/j.dsp.2026.106033_bib0060","article-title":"Crop leaf disease detection with additive gated convolution and hierarchical attention fusion","volume":"15","author":"Liu","year":"2025","journal-title":"Sci. Rep."},{"key":"10.1016\/j.dsp.2026.106033_bib0061","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"13733","article-title":"Repvgg: making vgg-style convnets great again","author":"Ding","year":"2021"},{"key":"10.1016\/j.dsp.2026.106033_bib0062","series-title":"2021 IEEE International Conference on Multimedia & Expo Workshops (ICMEW)","first-page":"1","article-title":"A dataset and benchmark of underwater object detection for robot picking","author":"Liu","year":"2021"},{"key":"10.1016\/j.dsp.2026.106033_bib0063","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops","first-page":"18","article-title":"Detection of marine animals in a new underwater dataset with varying visibility","author":"Pedersen","year":"2019"},{"key":"10.1016\/j.dsp.2026.106033_bib0064","first-page":"107984","article-title":"Yolov10: real-time end-to-end object detection","volume":"37","author":"Wang","year":"2024","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.dsp.2026.106033_bib0065","unstructured":"W. Lv, Y. Zhao, Q. Chang, K. Huang, G. Wang, Y. Liu, Rt-detrv2: Improved baseline with bag-of-freebies for real-time detection transformer, (2024). arXiv: 2407.17140."},{"key":"10.1016\/j.dsp.2026.106033_bib0066","unstructured":"Y. Peng, H. Li, P. Wu, Y. Zhang, X. Sun, F. Wu, D-FINE: Redefine regression task in DETRs as fine-grained distribution refinement, arXiv: 2410.13842(2024). 10.48550\/arXiv.2410.13842."},{"key":"10.1016\/j.dsp.2026.106033_bib0067","series-title":"Proceedings of the Computer Vision and Pattern Recognition Conference","first-page":"15162","article-title":"Deim: detr with improved matching for fast convergence","author":"Huang","year":"2025"},{"key":"10.1016\/j.dsp.2026.106033_bib0068","first-page":"1","article-title":"Low visibility underwater biological target detection based on the improved YOLOV5s: h. lin et al","author":"Lin","year":"2025","journal-title":"Vis. Comput."},{"key":"10.1016\/j.dsp.2026.106033_bib0069","doi-asserted-by":"crossref","DOI":"10.1016\/j.optlastec.2025.114357","article-title":"EAMSF-DETR: Edge-aware multi-scale feature fusion network based on DETR for underwater object detection","volume":"194","author":"Li","year":"2026","journal-title":"Optics Laser Technol."}],"container-title":["Digital Signal Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1051200426001521?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1051200426001521?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T03:39:41Z","timestamp":1777606781000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1051200426001521"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6]]},"references-count":69,"alternative-id":["S1051200426001521"],"URL":"https:\/\/doi.org\/10.1016\/j.dsp.2026.106033","relation":{},"ISSN":["1051-2004"],"issn-type":[{"value":"1051-2004","type":"print"}],"subject":[],"published":{"date-parts":[[2026,6]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"UCOE-DETR: An accurate detection transformer with underwater characteristic-oriented encoder","name":"articletitle","label":"Article Title"},{"value":"Digital Signal Processing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.dsp.2026.106033","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"106033"}}