{"id":"https://openalex.org/W7127048808","doi":"https://doi.org/10.3724/j.1007-6336.2024-x-0311","title":"An improved YOLOv8-based method for litter identification in drone shoreline images","display_name":"An improved YOLOv8-based method for litter identification in drone shoreline images","publication_year":2026,"publication_date":"2026-02-02","ids":{"openalex":"https://openalex.org/W7127048808","doi":"https://doi.org/10.3724/j.1007-6336.2024-x-0311"},"language":"en","primary_location":{"id":"doi:10.3724/j.1007-6336.2024-x-0311","doi":"https://doi.org/10.3724/j.1007-6336.2024-x-0311","is_oa":false,"landing_page_url":"https://doi.org/10.3724/j.1007-6336.2024-x-0311","pdf_url":null,"source":{"id":"https://openalex.org/S4306519218","display_name":"Marine Environmental Science","issn_l":"1007-6336","issn":["1007-6336"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Marine Environmental Science","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Fan Yang","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fan Yang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123983322","display_name":"Yanlong CHEN","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yanlong Chen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5123994682","display_name":"Shanwei LIU","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shanwei Liu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06436218,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"45","issue":"2","first_page":"304","last_page":"311"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9779999852180481,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9779999852180481,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.011900000274181366,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10753","display_name":"Microplastics and Plastic Pollution","score":0.006800000090152025,"subfield":{"id":"https://openalex.org/subfields/2310","display_name":"Pollution"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/uav-imagery","display_name":"UAV imagery","score":0.7889999747276306},{"id":"https://openalex.org/keywords/yolov8","display_name":"YOLOv8","score":0.9810000061988831},{"id":"https://openalex.org/keywords/lightweight-object-detection","display_name":"lightweight object detection","score":0.7080000042915344},{"id":"https://openalex.org/keywords/dysample-upsampling","display_name":"DySample upsampling","score":0.9259999990463257},{"id":"https://openalex.org/keywords/cbam-attention-module","display_name":"CBAM attention mechanism","score":0.9190000295639038}],"concepts":[{"id":"https://openalex.org/C59519942","wikidata":"https://www.wikidata.org/wiki/Q650665","display_name":"Drone","level":2,"score":0.7028999924659729},{"id":"https://openalex.org/C152382732","wikidata":"https://www.wikidata.org/wiki/Q468756","display_name":"Shore","level":2,"score":0.5925999879837036},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5512999892234802},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.535099983215332},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.41929998993873596},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.3393999934196472},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3240000009536743},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3133000135421753},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.2919999957084656},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.25949999690055847},{"id":"https://openalex.org/C62329434","wikidata":"https://www.wikidata.org/wiki/Q463960","display_name":"Marine debris","level":3,"score":0.2542000114917755}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3724/j.1007-6336.2024-x-0311","doi":"https://doi.org/10.3724/j.1007-6336.2024-x-0311","is_oa":false,"landing_page_url":"https://doi.org/10.3724/j.1007-6336.2024-x-0311","pdf_url":null,"source":{"id":"https://openalex.org/S4306519218","display_name":"Marine Environmental Science","issn_l":"1007-6336","issn":["1007-6336"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Marine Environmental Science","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W2086454592","https://openalex.org/W2802213413","https://openalex.org/W2895805893","https://openalex.org/W2920619868","https://openalex.org/W2962710355","https://openalex.org/W3016810880","https://openalex.org/W3123775691","https://openalex.org/W3162651833","https://openalex.org/W4388915117"],"related_works":[],"abstract_inverted_index":{"\u672c\u6587\u5229\u7528\u6cb3\u5317\u7701\u5510\u5c71\u5e02\u5cb8\u6ee9\u5783\u573e\u65e0\u4eba\u673a\u6b63\u5c04\u5f71\u50cf\u6570\u636e\uff0c\u57fa\u4e8eYOLOv8\u6a21\u578b\uff0c\u901a\u8fc7\u4f7f\u7528\u8f7b\u91cf\u7ea7\u4e0a\u91c7\u6837\u7b97\u5b50DySample\u3001\u52a0\u5165CBAM\u6ce8\u610f\u529b\u673a\u5236\u3001\u7ed3\u5408\u635f\u5931\u51fd\u6570Poweful-IoU\u7b49\u65b9\u6cd5\u63d0\u9ad8\u6a21\u578b\u68c0\u6d4b\u7cbe\u5ea6\uff0c\u63d0\u51fa\u4e00\u79cd\u9002\u7528\u4e8e\u5cb8\u6ee9\u5783\u573e\u68c0\u6d4b\u7684\u8bc6\u522b\u6a21\u578b\uff08YOLOv8-b\uff09\u3002\u5728\u81ea\u5efa\u6570\u636e\u96c6\u4e0a\u7684\u5b9e\u9a8c\u7ed3\u679c\u8868\u660e\uff0c\u4e0e\u57fa\u7840\u6a21\u578bYOLOv8\u76f8\u6bd4\uff0cYOLOv8-b\u6a21\u578b\u51c6\u786e\u7387\u63d0\u53472.1%\uff0c\u53ec\u56de\u7387\u63d0\u53471.9%\uff0cmAP\u63d0\u53471%\uff0c\u4e14\u8be5\u6a21\u578b\u5bf94\u7c7b\u5cb8\u6ee9\u5783\u573e\u6709\u826f\u597d\u7684\u8bc6\u522b\u80fd\u529b\uff0c\u5bf9\u5404\u7c7b\u5783\u573e\u7684\u8bc6\u522b\u7cbe\u5ea6\u5747\u8fbe\u523090%\u4ee5\u4e0a\u3002\u540c\u65f6\uff0c\u5e94\u7528\u8be5\u6a21\u578b\u5bf9\u5510\u5c71\u6e7e\u4e00\u5904\u5cb8\u6ee9\u8fdb\u884c\u6d4b\u8bd5\u5e76\u53d6\u5f97\u826f\u597d\u7684\u5cb8\u6ee9\u5783\u573e\u8bc6\u522b\u6548\u679c\u3002YOLOv8-b\u6a21\u578b\u53ef\u6ee1\u8db3\u65e0\u4eba\u673a\u5f71\u50cf\u4e2d\u5783\u573e\u7684\u5b9a\u4f4d\u4e0e\u8bc6\u522b\u9700\u6c42\uff0c\u4e3a\u5cb8\u6ee9\u5783\u573e\u7684\u4e1a\u52a1\u5316\u76d1\u6d4b\u63d0\u4f9b\u76f8\u5e94\u7684\u6280\u672f\u652f\u6301\u3002":[0]},"counts_by_year":[],"updated_date":"2026-09-27T08:07:27.782135","created_date":"2026-02-03T00:00:00"}
