ArticleSensors (Basel, Switzerland)2022
Insulator-Defect Detection Algorithm Based on Improved YOLOv7.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- SE-Attention Augmented Hybrid CNN-BiLSTM Model for Leakage Current-Based Detection of Cracked and Broken High-Voltage Porcelain Insulators.Biomimetics (Basel, Switzerland) · 2026Article
- Enhancements and On-Site Experimental Study on Fall Detection Algorithm for Students in Campus Staircase.Sensors (Basel, Switzerland) · 2025Article
- FSCA-YOLO: An Enhanced YOLO-Based Model for Multi-Target Dairy Cow Behavior Recognition.Animals : an open access journal from MDPI · 2025Article
- Improved Aerial Surface Floating Object Detection and Classification Recognition Algorithm Based on YOLOv8n.Sensors (Basel, Switzerland) · 2025Article
- Detection of hydrophobicity grade of insulators based on AHC-YOLO algorithm.Scientific reports · 2025Article
- Insulator Defect Detection Algorithm Based on Improved YOLOv11n.Sensors (Basel, Switzerland) · 2025Article
- An insulator target detection algorithm based on improved YOLOv5.Scientific reports · 2025Article
- An optimized transformer model for efficient detection of thoracic diseases in chest X-rays with multi-scale feature fusion.PloS one · 2025Article
- SCI-YOLO11: An improved defect detection algorithm for transmission line insulators based on YOLO11.PloS one · 2025Article
- Article
- Research on Automatic Recognition of Dairy Cow Daily Behaviors Based on Deep Learning.Animals : an open access journal from MDPI · 2024Article
- Research on surface defect detection algorithm of pipeline weld based on YOLOv7.Scientific reports · 2024Article
- Article
- Research on vehicle detection based on improved YOLOX_S.Scientific reports · 2023Article
- FS-RSDD: Few-Shot Rail Surface Defect Detection with Prototype Learning.Sensors (Basel, Switzerland) · 2023Article
- ESAMask: Real-Time Instance Segmentation Fused with Efficient Sparse Attention.Sensors (Basel, Switzerland) · 2023Article
- Group Method of Data Handling Using Christiano-Fitzgerald Random Walk Filter for Insulator Fault Prediction.Sensors (Basel, Switzerland) · 2023Article
- Rock Crack Recognition Technology Based on Deep Learning.Sensors (Basel, Switzerland) · 2023Article
- Tea leaf disease detection and identification based on YOLOv7 (YOLO-T).Scientific reports · 2023Article
- ID-YOLOv7: an efficient method for insulator defect detection in power distribution network.Frontiers in neurorobotics · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Existing detection methods face a huge challenge in identifying insulators with minor defects when targeting transmission line images with complex backgrounds. To ensure the safe operation of transmission lines, an improved YOLOv7 model is proposed to improve detection results. Firstly, the target boxes of the insulator dataset are clustered based on K-means++ to generate more suitable anchor boxes for detecting insulator-defect targets. Secondly, the Coordinate Attention (CoordAtt) module and HorBlock module are added to the network. Then, in the channel and spatial domains, the network can enhance the effective features of the feature-extraction process and weaken the ineffective features. Finally, the SCYLLA-IoU (SIoU) and focal loss functions are used to accelerate the convergence of the model and solve the imbalance of positive and negative samples. Furthermore, to optimize the overall performance of the model, the method of non-maximum suppression (NMS) is improved to reduce accidental deletion and false detection of defect targets. The experimental results show that the mean average precision of our model is 93.8%, higher than the Faster R-CNN model, the YOLOv7 model, and YOLOv5s model by 7.6%, 3.7%, and 4%, respectively. The proposed YOLOv7 model can effectively realize the accurate detection of small objects in complex backgrounds.
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