ArticleSensors (Basel, Switzerland)2022
Semi-ProtoPNet Deep Neural Network for the Classification of Defective Power Grid Distribution Structures.
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 10 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial Intelligence of Things Applied to Assistive Technology: A Systematic Literature Review.Sensors (Basel, Switzerland) · 2022Pooled it
- The shallowest transparent and interpretable deep neural network for image recognition.Scientific reports · 2025Article
- A Review of Automation and Sensors: Parameter Control of Thermal Treatments for Electrical Power Generation.Sensors (Basel, Switzerland) · 2024Review
- Video-Based Human Activity Recognition Using Deep Learning Approaches.Sensors (Basel, Switzerland) · 2023Article
- Study on Slagging Characteristics of Boiler Pre-combustion Chambers Based on Deep Learning.ACS omega · 2023Article
- Optimized EWT-Seq2Seq-LSTM with Attention Mechanism to Insulators Fault Prediction.Sensors (Basel, Switzerland) · 2023Article
- A New Approach to Optimize SVM for Insulator State Identification Based on Improved PSO Algorithm.Sensors (Basel, Switzerland) · 2022Article
- Wavelet LSTM for Fault Forecasting in Electrical Power Grids.Sensors (Basel, Switzerland) · 2022Article
- An Architecture for Managing Data Privacy in Healthcare with Blockchain.Sensors (Basel, Switzerland) · 2022Article
- Fault Prediction Based on Leakage Current in Contaminated Insulators Using Enhanced Time Series Forecasting Models.Sensors (Basel, Switzerland) · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Power distribution grids are typically installed outdoors and are exposed to environmental conditions. When contamination accumulates in the structures of the network, there may be shutdowns caused by electrical arcs. To improve the reliability of the network, visual inspections of the electrical power system can be carried out; these inspections can be automated using computer vision techniques based on deep neural networks. Based on this need, this paper proposes the Semi-ProtoPNet deep learning model to classify defective structures in the power distribution networks. The Semi-ProtoPNet deep neural network does not perform convex optimization of its last dense layer to maintain the impact of the negative reasoning process on image classification. The negative reasoning process rejects the incorrect classes of an input image; for this reason, it is possible to carry out an analysis with a low number of images that have different backgrounds, which is one of the challenges of this type of analysis. Semi-ProtoPNet achieves an accuracy of 97.22%, being superior to VGG-13, VGG-16, VGG-19, ResNet-34, ResNet-50, ResNet-152, DenseNet-121, DenseNet-161, DenseNet-201, and also models of the same class such as ProtoPNet, NP-ProtoPNet, Gen-ProtoPNet, and Ps-ProtoPNet.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.