NCBI PubMed Central
open access
High-Sensitivity Identification of Micro-Voids at Thick Steel Shell-Concrete Interfaces Using Elastic Wave Analysis and Feature Attention Mechanisms.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- TEEP-RCNN: Texture-Enhanced Edge-aware Perception for Steel Surface Defect Detection via Improved Convolutional Block Attention in Faster R-CNN#1064621
- Ultrasonic Imaging and the Long Wavelength Phase#964028
- Vision-Based Tactile Sensing for the Perception of the Object's Compliance and Hardness#925824
- EdgeCrafter: Compact ViTs for Edge Dense Prediction via Task-Specialized Distillation#614960
- EdgeCrafter: Compact ViTs for Edge Dense Prediction via Task-Specialized Distillation#613993
Record · ID 427999
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive