35 citations · 39 across the 6 of their papers we have counts for
6 papers
Reservoir-enhanced Segment Anything Model for Subsurface Diagnosis
Xiren Zhou, Shikang Liu, Xinyu Yan +5
Urban roads and infrastructure, vital to city operations, face growing threats from subsurface anomalies like cracks and cavities. Ground Penetrating Radar (GPR) effectively visual…
MTMT: Consolidating Multiple Thinking Modes to Form a Thought Tree for Strengthening LLM
Changcheng Li, Xiangyu Wang, Qiuju Chen +2
Large language models (LLMs) have shown limitations in tasks requiring complex logical reasoning and multi-step problem-solving. To address these challenges, researchers have emplo…
Underground Diagnosis Based on GPR and Learning in the Model Space
Ao Chen, Xiren Zhou, Yizhan Fan +1
Ground Penetrating Radar (GPR) has been widely used in pipeline detection and underground diagnosis. In practical applications, the characteristics of the GPR data of the detected…
Improving the Anomaly Detection in GPR Images by Fine-Tuning CNNs with Synthetic Data
Xiren Zhou, Shikang Liu, Ao Chen +2
Ground Penetrating Radar (GPR) has been widely used to estimate the healthy operation of some urban roads and underground facilities. When identifying subsurface anomalies by GPR i…
Mapping the Buried Cable by Ground Penetrating Radar and Gaussian-Process Regression
Xiren Zhou, Qiuju Chen, Shengfei Lyu +1
With the rapid expansion of urban areas and the increasingly use of electricity, the need for locating buried cables is becoming urgent. In this paper, a noval method to locate und…
Estimating the Direction and Radius of Pipe from GPR Image by Ellipse Inversion Model
Xiren Zhou, Qiuju Chen, Shengfei Lyu +1
Ground Penetrating Radar (GPR) is widely used as a non-destructive approach to estimate buried utilities. When the GPR's detecting direction is perpendicular to a pipeline, a hyper…