Cracked insulator detection based on r-fcn

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August undefined, 2024

WebMay 20, 2016 · We present region-based, fully convolutional networks for accurate and efficient object detection. In contrast to previous region-based detectors such as Fast/Faster R-CNN that apply a costly per-region …

Insulators’ Identification and Missing Defect Detection in Aerial ...

WebFeb 19, 2024 · The most beneficial results were obtained for two convolutional neural networks: the faster region-convolutional neural network (faster R-CNN) and the region-based fully convolutional network (R-FCN). Faster R-CNN reached the highest AP (average precision) at a level of 0.8 for 60 frames. WebFor the same task, Liu et al. proposed a means based on R-FCN. Online hard example mining, sample adjusting, and soft NMS were employed to promote the performance of R-FCN. The above research of multidevice detection indicates that deep learning-based detection algorithms have a good generalization ability. riverchase galleria birmingham hotel

Insulator Detection Method in Inspection Image Based on Impr

WebJun 1, 2024 · The results show that the proposed method can realize effective detection of insulators and achieve a precision of 94% and a recall of 88% on the testing dataset … WebAug 1, 2024 · Based on the extracted insulator strings, we change the problem to cracked insulators detection under complex conditions with … WebMar 28, 2024 · The detection of insulators in power transmission and transformation inspection images is the basis for insulator state detection and fault diagnosis in … riverchase galleria birmingham stores

Cracked Insulator Detection Based on R-FCN

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WebRegion-based Fully Convolutional Networks, or R-FCNs, are a type of region-based object detector. In contrast to previous region-based object detectors such as Fast/ Faster R-CNN that apply a costly per-region … WebApr 7, 2024 · Cracks are often the most intuitive indicators for assessing the condition of in-service structures. Intelligent detection methods based on regular convolutional neural networks (CNNs) have been widely applied to the field of crack detection in recently years; however, these methods exhibit unsatisfying performance on the detection of out-of … smith signsWebApr 1, 2024 · The improved one-dimensional Hough transform detection algorithm is used to identify the ellipse in the edge image, that is, the insulator. The decision conditions of fault identification are designed to complete the fault identification of insulator drop. riverchase galleria hoover al all elevators

"WebIn civil engineering, the stability of concrete is of great significance to safety of people’s life and property, so it is necessary to detect concrete damage effectively. In this paper, we treat crack detection on concrete surface as a semantic segmentation task that distinguishes background from crack at the pixel level. Inspired by Fully … " - Cracked insulator detection based on r-fcn

Cracked insulator detection based on r-fcn

Insulators’ Identification and Missing Defect Detection in Aerial ...

WebJul 14, 2024 · An aircraft engine blade surface defect detection method based on deep learning is characterized by comprising the following steps: s1, collecting an image of the blade of the aircraft engine,... WebAn insulator defect detection method based on improved ResNeSt and Region Proposal Network (RPN) was proposed. First, this method builds a new network based on …

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WebAug 1, 2024 · The insulator is an important component of the high voltage transmission line. Inspecting the defects of the insulator plays an important role in ensuring the … WebFaster R-CNN : Insulator: The average precision at a level of 0.8 for 60 frames: R-FCN : Cracked insulator detection: The average accuracy rate of 90.5%: Mask R-CNN : …

WebMar 28, 2024 · Insulator Detection Under Mutual Occlusion Non-maximum suppression (NMS) is a widely applied post-processing algorithm to perform redundant removal in object detections. The traditional NMS which performs greedy clustering based on a fixed threshold is manually designed. WebMay 2, 2024 · The average precision of the modified YOLOv3 (YOLOv3-dense) model is 94.47%, and the average running time of per image can reach 8.5 ms, however, the modified model can only perform the localization detection of insulators, which is not used for the research of insulator defect detection.

WebThis paper, focusing on the self-blast glass insulator, proposes a deep learning solution. We address the broken insulators location problem as a low signal-noise-ratio image location framework with two modules: 1) object detection based on Fast R-CNN, and 2) classiﬁcation of pixels based on U-net. WebThe traditional cracked insulator detection method is to use image denoising, single insulator disk segmentation, and the adjacent European distance to locate and identify …

WebTable 1 Insulators’ Identification and Missing Defect Detection in Aerial Images Based on Cascaded YOLO Models Computational Intelligence and Neuroscience Journal overview For authors For reviewers For editors Table of Contents Special Issues Computational Intelligence and Neuroscience / 2024 / Article / Tab 1 Research Article

WebThe traditional cracked insulator detection method is to use image denoising, single insulator disk segmentation, and the adjacent European distance to locate and identify cracked insulators. Experiments show that the robustness of these methods is poor and their ability to adapt to the environment is not good. riverchase galleria mall in hoover alWebSep 23, 2024 · 2.1 Two-stage detection algorithm 2.1.1 Region-based convolutional neural network. In 2014, Girshick et al. (2013) proposed the R-CNN algorithm. R-CNN changed … riverchase galleria mall hoursWebOct 17, 2024 · Crack plays a critical role in the field of evaluating the quality of concrete structures, which affects the safety, applicability, and durability of the structure. Due to its excellent performance in image processing, the convolutional neural network is becoming the mainstream choice to replace manual crack detection. In this paper, we improve the … riverchase galleria mall hotelWebSep 23, 2024 · The R-FCN adopts a residual network ( He et al., 2016) as a fully convolutional image classifier backbone. It uses a position-sensitive mapping map RoI pool to coordinate the translation invariance and sensitivity across the convolutional layers, improving object localization. 2.1.6 Light head region-based convolutional neural network smith signal helmet reviewWebFeb 3, 2024 · The Exact R-CNN (exact region-based convolutional neural network) is then used to detect insulator defects in the second stage. Compared with the traditional target detection method, this two-stage pipeline can greatly eliminate the interference of background features on the target detection, and greatly improve the accuracy of target … smith signs tulareWebOct 1, 2024 · An algorithm that detect the insulators' self-detonation defect based on deep learning reaches more than 99%, and the intelligent design effectively improves the efficiency of the power transmission system. Insulators are exerting an important influence in transmission lines. The timely detection of insulator explosion defects is an important … smith significationWebThe traditional cracked insulator detection method is to use image denoising, single insulator disk segmentation, and the adjacent European distance to locate and identify cracked … smith signs bend oregon