ArticleSensors (Basel, Switzerland)2024
EcoDetect-YOLO: A Lightweight, High-Generalization Methodology for Real-Time Detection of Domestic Waste Exposure in Intricate Environmental Landscapes.
Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- A Lightweight End-to-End Framework for Real-Time Vehicle-Ejected Debris Detection on Edge Devices.Sensors (Basel, Switzerland) · 2026Article
- SPR-DETR: DETR with Self-Supervised Learning and Position Relation Modeling for UAV-Based Catenary Support Component Detection in Electrified Railways.Sensors (Basel, Switzerland) · 2026Article
- FedMIR: Multimodal Federated Learning with Missing Modality Imputation and Distribution-Aware Routing.Sensors (Basel, Switzerland) · 2026Article
- Improving performance for multi-category anthropogenic debris detection in river environments by using a size-tailored annotation approach and data augmentation.Scientific reports · 2026Article
- Deep learning for construction waste detection using ConvNeXt V2 EMA attention and WIoU v3 loss.Scientific reports · 2026Article
- Confidence-gradient reweighting and lightweight feature enhancement algorithm for steel surface defect detection.Scientific reports · 2026Article
- Improved faster R-CNN for steel surface defect detection in industrial quality control.Scientific reports · 2025Article
- PEYOLO a perception efficient network for multiscale surface defects detection.Scientific reports · 2025Article
- RSW-YOLO: A Vehicle Detection Model for Urban UAV Remote Sensing Images.Sensors (Basel, Switzerland) · 2025Article
- RSTD-YOLOv7: a steel surface defect detection based on improved YOLOv7.Scientific reports · 2025Article
- EcoDetect-YOLOv2: A High-Performance Model for Multi-Scale Waste Detection in Complex Surveillance Environments.Sensors (Basel, Switzerland) · 2025Article
- Research on underwater disease target detection method of inland waterway based on deep learning.Scientific reports · 2025Article
- A Lightweight Strip Steel Surface Defect Detection Network Based on Improved YOLOv8.Sensors (Basel, Switzerland) · 2024Article
Corrections and comments
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Authors and funding
6 authors.
Funding
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's efficacy in identifying small garbage targets. Lastly, a bidirectional feature pyramid network (BiFPN) is introduced to strengthen the model's capability for deep feature fusion. Experimental results demonstrate EcoDetect-YOLO's 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 mAP
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