{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T16:23:52Z","timestamp":1780503832154,"version":"3.54.1"},"reference-count":33,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Key Research and Development Program of Hainan Province","award":["ZDYF2024GXJS034"],"award-info":[{"award-number":["ZDYF2024GXJS034"]}]},{"name":"Major Science and Technology Program of Yazhou Bay Innovation Institute, Hainan Tropical Ocean University","award":["2023CXYZD001"],"award-info":[{"award-number":["2023CXYZD001"]}]},{"name":"School-Level Research and Practice Project of Hainan Tropical Ocean University","award":["RHYxgnw2024-12"],"award-info":[{"award-number":["RHYxgnw2024-12"]}]},{"name":"Sanya Science and Technology Special Fund","award":["2022KJCX30"],"award-info":[{"award-number":["2022KJCX30"]}]},{"name":"Hainan Provincial Graduate Student Innovation Research Project","award":["Hys2025-523"],"award-info":[{"award-number":["Hys2025-523"]}]},{"name":"University-Level Graduate Innovation Research Projects of Hainan Tropical Ocean University","award":["RHDYC-202514"],"award-info":[{"award-number":["RHDYC-202514"]}]},{"name":"University-Level Graduate Innovation Research Projects of Hainan Tropical Ocean University","award":["RHDYC-202515"],"award-info":[{"award-number":["RHDYC-202515"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>Efficient object detection is vital for Remotely Operated Vehicles (ROVs) performing marine debris cleanup, yet existing lightweight designs frequently encounter efficiency bottlenecks when adapted to deeper neural networks. This research identifies a critical \u201cInverted Bottleneck\u201d anomaly in the Slim-Neck architecture on the YOLO11 backbone, where deep-layer Memory Access Cost (MAC) abnormally spikes. To address this, we propose SvelteNeck-YOLO. By incorporating the proposed EHSCSP module and EHConv operator, the model systematically eliminates computational redundancies. Empirical validation on the TrashCan and URPC2019 datasets demonstrates that the model resolves the memory wall issue, achieving a state-of-the-art trade-off with only 5.8 GFLOPs. Specifically, it delivers a 34% relative reduction in computational load compared to specialized underwater models while maintaining a superior Recall of 0.859. Consequently, SvelteNeck-YOLO establishes a robust, cross-generational solution, optimizing the Pareto frontier between inference speed and detection sensitivity for resource-constrained underwater edge computing.<\/jats:p>","DOI":"10.3390\/a19020113","type":"journal-article","created":{"date-parts":[[2026,2,2]],"date-time":"2026-02-02T09:00:33Z","timestamp":1770022833000},"page":"113","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["SvelteNeck by EHConv: A Cross-Generational Lightweight Neck for Real-Time Object Detection"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-5766-9278","authenticated-orcid":false,"given":"Tianyi","family":"Wang","sequence":"first","affiliation":[{"name":"Yazhou Bay Innovation Institute, Hainan Tropical Ocean University, Sanya 572025, China"},{"name":"School of Computer Science and Technology, Hainan Tropical Ocean University, Sanya 572022, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8298-9726","authenticated-orcid":false,"given":"Haifeng","family":"Wang","sequence":"additional","affiliation":[{"name":"Yazhou Bay Innovation Institute, Hainan Tropical Ocean University, Sanya 572025, China"},{"name":"School of Computer Science and Technology, Hainan Tropical Ocean University, Sanya 572022, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenbin","family":"Wang","sequence":"additional","affiliation":[{"name":"Yazhou Bay Innovation Institute, Hainan Tropical Ocean University, Sanya 572025, China"},{"name":"School of Computer Science and Technology, Hainan Tropical Ocean University, Sanya 572022, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9195-8000","authenticated-orcid":false,"given":"Kun","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Information Science and Technology, Hainan Normal University, Haikou 571158, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-8815-9141","authenticated-orcid":false,"given":"Baojiang","family":"Ye","sequence":"additional","affiliation":[{"name":"Yazhou Bay Innovation Institute, Hainan Tropical Ocean University, Sanya 572025, China"},{"name":"School of Computer Science and Technology, Hainan Tropical Ocean University, Sanya 572022, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-3901-8171","authenticated-orcid":false,"given":"Huilin","family":"Dong","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Hainan Tropical Ocean University, Sanya 572022, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,2,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"242","DOI":"10.1007\/s10462-024-10877-1","article-title":"A Comprehensive Survey of Deep Learning-Based Lightweight Object Detection Models for Edge Devices","volume":"57","author":"Mittal","year":"2024","journal-title":"Artif. 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