Research graph
References from CEC-YOLO: a floating-debris detection algorithm for complex water-surface environments. Local targets link to admitted publications; unresolved targets remain external evidence.
YOLOv4: optimal speed and accuracy of object detection
2020 · External reference
End-to-end object detection with transformers
2020 · External reference
Autonomous water quality monitoring and water surface cleaning for unmanned surface vehicle
10.3390/s21041102 · 2021 · External reference
Water surface garbage detection based on lightweight YOLOv5
10.1038/s41598-024-55051-3 · 2024 · External reference
Xception: deep learning with depthwise separable convolutions
2017 · External reference
Class-balanced loss based on effective number of samples
2019 · External reference
Deformable convolutional networks
2017 · External reference
ATT-YOLOv5-Ghost: water surface object detection in complex scenes
10.1007/s11554-023-01354-z · 2023 · External reference
SS-YOLOv8: a lightweight algorithm for surface litter detection
10.3390/app14209283 · 2024 · External reference
Rich feature hierarchies for accurate object detection and semantic segmentation
2014 · External reference
Improved YOLOv5s and transfer learning for floater detection
10.1177/00368504251342075 · 2025 · External reference
GhostNet: more features from cheap operations
2020 · External reference
EC-YOLOX: a deep-learning algorithm for floating objects detection in ground images of complex water environments
10.1109/jstars.2024.3367713 · 2024 · External reference
Deep residual learning for image recognition
2016 · External reference
MobileNets: efficient convolutional neural networks for mobile vision applications
2017 · External reference
Squeeze-and-excitation networks
2018 · External reference
Densely connected convolutional networks
2017 · External reference
Plastic waste inputs from land into the ocean
10.1126/science.1260352 · 2015 · External reference
APM-YOLOv7 for small-target water-floating garbage detection based on multi-scale feature adaptive weighted fusion
10.3390/s24010050 · 2024 · External reference
Unresolved reference
External reference
Unresolved reference
External reference
Construction of a real-time detection for floating plastics in a stream using video cameras and deep learning
10.3390/s25072225 · 2025 · External reference
Context and spatial feature calibration for real-time semantic segmentation
10.1109/tip.2023.3318967 · 2023 · External reference
TC-YOLOv5: rapid detection of floating debris on Raspberry Pi 4B
10.1007/s11554-023-01265-z · 2023 · External reference
A floating-waste-detection method for unmanned surface vehicle based on feature fusion and enhancement
10.3390/jmse11122234 · 2023 · External reference
DENS-YOLOv6: a small object detection model for garbage detection on water surface
10.1007/s11042-023-17679-7 · 2024 · External reference
Detection of floating objects on water surface using YOLOv5s in an edge computing environment
10.3390/w16010086 · 2024 · External reference
PAR-YOLO: a precise and real-time YOLO water surface garbage detection model
10.1007/s12145-024-01679-8 · 2025 · External reference
Improved YOLO based detection algorithm for floating debris in waterway
10.3390/e23091111 · 2021 · External reference
Microsoft COCO: common objects in context
2014 · External reference
SSD: single shot multibox detector
2016 · External reference
Path aggregation network for instance segmentation
2018 · External reference
GCEA-YOLO: an enhanced YOLOv11-based network for smoking behavior detection in oilfield operation areas
10.3390/s26010103 · 2025 · External reference
An annotated dataset and benchmark for detecting floating debris in inland waters
10.1038/s41597-025-04594-9 · 2025 · External reference
You only look once: unified, real-time object detection
2016 · External reference
YOLO9000: better, faster, stronger
2017 · External reference
YOLOv3: an incremental improvement
2018 · External reference
Faster R-CNN: towards real-time object detection with region proposal networks
2015 · External reference
MobileNetV2: inverted residuals and linear bottlenecks
2018 · External reference
Export of plastic debris by rivers into the sea
10.1021/acs.est.7b02368 · 2017 · External reference
YOLO-based real-time floating debris counting in urban rivers for flood monitoring and water resource management
10.1007/s10661-026-15040-7 · 2026 · External reference
YOLOv7: trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
2023 · External reference
Non-local neural networks
2018 · External reference
CSPNet: a new backbone that can enhance learning capability of CNN
2020 · External reference
ECA-Net: efficient channel attention for deep convolutional neural networks
2020 · External reference
A lightweight context-aware framework for toxic mushroom detection in complex ecological environments
10.1016/j.ecoinf.2025.103256 · 2025 · External reference
CBAM: convolutional block attention module
2018 · External reference
Development of a lightweight floating object detection algorithm
10.3390/w16111633 · 2024 · External reference
Detecting tiny objects in aerial images: a normalized Wasserstein distance and a new benchmark
10.1016/j.isprsjprs.2022.06.002 · 2022 · External reference
Yolov5-ff: detecting floating objects on the surface of fresh water environments
10.3390/app13137367 · 2023 · External reference
Eyolov3: an efficient real-time detection model for floating object on river
10.3390/app13042303 · 2023 · External reference
River floating object detection with transformer model in real time
10.1038/s41598-025-93659-1 · 2025 · External reference
Shufflenet: an extremely efficient convolutional neural network for mobile devices
2018 · External reference
Detrs beat yolos on real-time object detection
2024 · External reference
Pyramid scene parsing network
2017 · External reference
Dualconv: dual convolutional kernels for lightweight deep neural networks
10.1109/tnnls.2022.3151138 · 2023 · External reference
YOLO-based real-time floating debris counting in urban rivers for flood monitoring and water resource management
10.1007/s10661-026-15040-7 · ExternalCitation · doi-reference
DENS-YOLOv6: a small object detection model for garbage detection on water surface
10.1007/s11042-023-17679-7 · ExternalCitation · doi-reference
TC-YOLOv5: rapid detection of floating debris on Raspberry Pi 4B
10.1007/s11554-023-01265-z · ExternalCitation · doi-reference
ATT-YOLOv5-Ghost: water surface object detection in complex scenes
10.1007/s11554-023-01354-z · ExternalCitation · doi-reference
PAR-YOLO: a precise and real-time YOLO water surface garbage detection model
10.1007/s12145-024-01679-8 · ExternalCitation · doi-reference
A lightweight context-aware framework for toxic mushroom detection in complex ecological environments
10.1016/j.ecoinf.2025.103256 · ExternalCitation · doi-reference
Detecting tiny objects in aerial images: a normalized Wasserstein distance and a new benchmark
10.1016/j.isprsjprs.2022.06.002 · ExternalCitation · doi-reference
Export of plastic debris by rivers into the sea
10.1021/acs.est.7b02368 · ExternalCitation · doi-reference
An annotated dataset and benchmark for detecting floating debris in inland waters
10.1038/s41597-025-04594-9 · ExternalCitation · doi-reference
Water surface garbage detection based on lightweight YOLOv5
10.1038/s41598-024-55051-3 · ExternalCitation · doi-reference
River floating object detection with transformer model in real time
10.1038/s41598-025-93659-1 · ExternalCitation · doi-reference
EC-YOLOX: a deep-learning algorithm for floating objects detection in ground images of complex water environments
10.1109/jstars.2024.3367713 · ExternalCitation · doi-reference
Context and spatial feature calibration for real-time semantic segmentation
10.1109/tip.2023.3318967 · ExternalCitation · doi-reference
Dualconv: dual convolutional kernels for lightweight deep neural networks
10.1109/tnnls.2022.3151138 · ExternalCitation · doi-reference
Plastic waste inputs from land into the ocean
10.1126/science.1260352 · ExternalCitation · doi-reference
Improved YOLOv5s and transfer learning for floater detection
10.1177/00368504251342075 · ExternalCitation · doi-reference
Eyolov3: an efficient real-time detection model for floating object on river
10.3390/app13042303 · ExternalCitation · doi-reference
Yolov5-ff: detecting floating objects on the surface of fresh water environments
10.3390/app13137367 · ExternalCitation · doi-reference
SS-YOLOv8: a lightweight algorithm for surface litter detection
10.3390/app14209283 · ExternalCitation · doi-reference
Improved YOLO based detection algorithm for floating debris in waterway
10.3390/e23091111 · ExternalCitation · doi-reference
A floating-waste-detection method for unmanned surface vehicle based on feature fusion and enhancement
10.3390/jmse11122234 · ExternalCitation · doi-reference
Autonomous water quality monitoring and water surface cleaning for unmanned surface vehicle
10.3390/s21041102 · ExternalCitation · doi-reference
APM-YOLOv7 for small-target water-floating garbage detection based on multi-scale feature adaptive weighted fusion
10.3390/s24010050 · ExternalCitation · doi-reference
Construction of a real-time detection for floating plastics in a stream using video cameras and deep learning
10.3390/s25072225 · ExternalCitation · doi-reference
GCEA-YOLO: an enhanced YOLOv11-based network for smoking behavior detection in oilfield operation areas
10.3390/s26010103 · ExternalCitation · doi-reference
Detection of floating objects on water surface using YOLOv5s in an edge computing environment
10.3390/w16010086 · ExternalCitation · doi-reference
Development of a lightweight floating object detection algorithm
10.3390/w16111633 · ExternalCitation · doi-reference
