HIGHLIGHTS
- who: Flaw Detection and collaborators from the School of Mechanical Engineering, Polytechnic University, China have published the research: Fully Convolutional Neural Network With GRU for 3D Braided Composite Material Flaw Detection, in the Journal: (JOURNAL)
- what: The authors propose a novel baseline model based on a fully convolution network (FCN) and gated recurrent unit (GRU) to classify ultrasonic signals from flawed 3D braided composite specimens with debonding defects. The aim of the ultrasonic inspection of engineering materials is to detect, locate and classify internal defects as quickly and accurately as possible. The multi-scale convolutional . . .
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