{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,23]],"date-time":"2025-04-23T08:09:02Z","timestamp":1745395742311,"version":"3.37.3"},"reference-count":62,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2024,7,18]],"date-time":"2024-07-18T00:00:00Z","timestamp":1721260800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100021171","name":"Guangdong Basic and Applied Basic Research Foundation","doi-asserted-by":"crossref","award":["2023A1515011326"],"id":[{"id":"10.13039\/501100021171","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100015600","name":"Guangdong Ocean University","doi-asserted-by":"crossref","award":["060302102101"],"id":[{"id":"10.13039\/501100015600","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Guangdong Provincial Science and Technology Innovation Strategy","award":["pdjh2023b0247"]},{"DOI":"10.13039\/501100013254","name":"National College Students Innovation and Entrepreneurship Training Program","doi-asserted-by":"crossref","award":["202410566027"],"id":[{"id":"10.13039\/501100013254","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Guangdong Ocean University Undergraduate Innovation Team","award":["CXTD2023014"]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"In response to the challenges of accurate identification and localization of garbage in intricate urban street environments, this paper proposes EcoDetect-YOLO, a garbage exposure detection algorithm based on the YOLOv5s framework, utilizing an intricate environment waste exposure detection dataset constructed in this study. Initially, a convolutional block attention module (CBAM) is integrated between the second level of the feature pyramid etwork (P2) and the third level of the feature pyramid network (P3) layers to optimize the extraction of relevant garbage features while mitigating background noise. Subsequently, a P2 small-target detection head enhances the model\u2019s efficacy in identifying small garbage targets. Lastly, a bidirectional feature pyramid network (BiFPN) is introduced to strengthen the model\u2019s capability for deep feature fusion. Experimental results demonstrate EcoDetect-YOLO\u2019s adaptability to urban environments and its superior small-target detection capabilities, effectively recognizing nine types of garbage, such as paper and plastic trash. Compared to the baseline YOLOv5s model, EcoDetect-YOLO achieved a 4.7% increase in mAP0.5, reaching 58.1%, with a compact model size of 15.7 MB and an FPS of 39.36. Notably, even in the presence of strong noise, the model maintained a mAP0.5 exceeding 50%, underscoring its robustness. In summary, EcoDetect-YOLO, as proposed in this paper, boasts high precision, efficiency, and compactness, rendering it suitable for deployment on mobile devices for real-time detection and management of urban garbage exposure, thereby advancing urban automation governance and digital economic development.<\/jats:p>","DOI":"10.3390\/s24144666","type":"journal-article","created":{"date-parts":[[2024,7,18]],"date-time":"2024-07-18T18:59:50Z","timestamp":1721329190000},"page":"4666","source":"Crossref","is-referenced-by-count":2,"title":["EcoDetect-YOLO: A Lightweight, High-Generalization Methodology for Real-Time Detection of Domestic Waste Exposure in Intricate Environmental Landscapes"],"prefix":"10.3390","volume":"24","author":[{"given":"Shenlin","family":"Liu","sequence":"first","affiliation":[{"name":"School of Mathematics and Computer, Guangdong Ocean University, Zhanjiang 524008, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-6912-4606","authenticated-orcid":false,"given":"Ruihan","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Mathematics and Computer, Guangdong Ocean University, Zhanjiang 524008, China"},{"name":"Artificial Intelligence Research Institute, International (Macau) Institute of Academic Research, Macau 999078, China"}]},{"given":"Minhua","family":"Ye","sequence":"additional","affiliation":[{"name":"College of Ocean Engineering and Energy, Guangdong Ocean University, Zhanjiang 524088, China"}]},{"given":"Jiawei","family":"Luo","sequence":"additional","affiliation":[{"name":"School of Mathematics and Computer, Guangdong Ocean University, Zhanjiang 524008, China"}]},{"given":"Derong","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Mathematics and Computer, Guangdong Ocean University, Zhanjiang 524008, China"}]},{"given":"Ming","family":"Dai","sequence":"additional","affiliation":[{"name":"School of Mathematics and Computer, Guangdong Ocean University, Zhanjiang 524008, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,7,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Kaza, S., Yao, L., Bhada-Tata, P., and Van Woerden, F. 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