Unmanned aerial vehicle power transmission line defect image detection method
The invention discloses an unmanned aerial vehicle power transmission line defect image detection method, relates to the technical field of power transmission defect identification, and realizes transplantation of a power transmission line defect identification neural network model to an unmanned ae...
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| creator | HU WEIJUN WU NENGCHENG CHENG XUMENG SU ZEWANG HUANG TIAOXIN CHEN GUANXIAN CHEN XI LIU XUANYOU |
| description | The invention discloses an unmanned aerial vehicle power transmission line defect image detection method, relates to the technical field of power transmission defect identification, and realizes transplantation of a power transmission line defect identification neural network model to an unmanned aerial vehicle edge end through cross-architecture migration of the power transmission line defect identification neural network model. An unmanned aerial vehicle mobile edge end is enabled for an intelligent inspection algorithm, online identification of power transmission line defects is supported, and power transmission line defect identification neural network pruning is performed on a power transmission line defect identification neural network model, so that a relatively high model compression ratio is realized, the precision loss of the pruned model is small, and the accuracy of the power transmission line defect identification neural network model is improved. And parameter quantification is carried out on th |
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An unmanned aerial vehicle mobile edge end is enabled for an intelligent inspection algorithm, online identification of power transmission line defects is supported, and power transmission line defect identification neural network pruning is performed on a power transmission line defect identification neural network model, so that a relatively high model compression ratio is realized, the precision loss of the pruned model is small, and the accuracy of the power transmission line defect identification neural network model is improved. 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An unmanned aerial vehicle mobile edge end is enabled for an intelligent inspection algorithm, online identification of power transmission line defects is supported, and power transmission line defect identification neural network pruning is performed on a power transmission line defect identification neural network model, so that a relatively high model compression ratio is realized, the precision loss of the pruned model is small, and the accuracy of the power transmission line defect identification neural network model is improved. 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An unmanned aerial vehicle mobile edge end is enabled for an intelligent inspection algorithm, online identification of power transmission line defects is supported, and power transmission line defect identification neural network pruning is performed on a power transmission line defect identification neural network model, so that a relatively high model compression ratio is realized, the precision loss of the pruned model is small, and the accuracy of the power transmission line defect identification neural network model is improved. And parameter quantification is carried out on th</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING PHYSICS |
| title | Unmanned aerial vehicle power transmission line defect image detection method |
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