Defect severity identification for a catenary system based on deep semantic learning

HIGHLIGHTS

  • who: Jian Wang and colleagues from the School of Electrical Engineering, Southwest Jiaotong University, Chengdu, China have published the Article: Defect Severity Identification for a Catenary System Based on Deep Semantic Learning, in the Journal: Sensors 2022, 22, 9922. of 16/Dec/2022
  • what: Motivated by the idea of ResNet and the deepening of word-level convolutional neural_networks (CNNs) , the authors propose a deep CNN algorithm that can efficiently capture long-range associations in text, which can extract richer semantics for domain-specific defect information identification and achieve superior performance by deepening the network without . . .

     

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