Takahiro Yamaguchi 교수

In this article, we focus on ground-penetrating radar (GPR) for subsurface utility pipe detection. Due to the dense and high-speed 3-D monitoring, GPR is a promising tool. However, because of enormous amount of radar data and difficulty of interpretation, inspection time and cost are the bottlenecks. In this article, we propose a novel detection algorithm by the combination of 3-D convolutional neural network (3-D-CNN) and Kirchhoff migration. A 3-D-CNN architecture was trained utilizing transve

In this article, an algorithm for detecting subsurface voids under the road from ground penetrating radar images is proposed. A multichannel radar system mounted on vehicle enables dense and highspeed monitoring. The novelty of the algorithm is a unique ElectroMagnetic simulation method and state-of-the-art deep learning technique to consider three-dimensional (3-D) reflection patterns of voids. To train deep learning models, 3-D reflection patterns were reproduced by 2-D finite difference time

In this paper, we focus on ground-penetrating radar (GPR) for infrastructural health monitoring, especially for the monitoring of reinforced concrete (RC) bridge slab. Due to the demand of noncontact and high-speed monitoring technique which can handle vast amounts of aging infrastructures, GPR is a promising tool. However, because radar images consist of many reflected waves, they are usually difficult to interpret. Furthermore, the spatial resolution of system is not enough considering the thi

Abstract— When moving images are displayed on matrix displays which reproduce gray levels utilizing pulse‐number/width‐modulation techniques, degradation of the gray levels and colors are often observed. The degradation originates from a temporal non‐uniformity of the light‐emission pattern, which is transformed into a spatial non‐uniformity of the light emission due to an after‐image effect of the eyes, which follow the image motion. The degradation becomes appreciable when the product of the s

Road cracks are a major concern for administrators. Visual inspection is labor-intensive. The accuracy of previous algorithms for detecting cracks in images requires improvement. Further, the length and thickness of cracks must be estimated. Light detection and ranging (Lidar), a standard smartphone feature is used to develop a method for the completely automatic, accurate, and quantitative evaluation of road cracks. The two contributions of this study are as follows. To achieve the highest segm

In this paper, a novel manhole and joint covers detection algorithm from radar images by Support Vector Machine (SVM) and Hough transform is proposed. Due to its dense and high-speed monitoring capabilities, Ground Penetrating Radar (GPR) is a promising tool. Furthermore, manhole and joint covers are apparent from surface reflections. An SVM model was developed utilizing Histogram of Oriented Gradient (HOG) feature and Laplacian filter. Classification accuracy of manhole, joint covers and paveme

The condition assessment of reinforced concrete (RC) bridge piers after an earthquake using measured responses is important for ensuring the safety of road and railway users. The problem is nonlinear, and the locations and extents of damages are various. However, previous research works focused on linear structural identification or model updating assuming a limited number of nonlinear materials for reasonable estimates. Leveraging the ability of deep learning (DL) for robustly estimating a larg

In this article, an algorithm for the automatic and quantitative evaluation of peeling and delamination on infrastructure surfaces from laser 3D point cloud data is proposed using state-of-the-art signal and image processing methodologies. A Mobile Mapping System (MMS) enables road administrators to collect the geometry of tunnel and road surfaces highspeed. The algorithm consists of two steps: 1D signal processing and 2D image processing. The peaks of anomalies are extracted by the envelope of

The presence of road cracks is an important indicator of damage. Deep learning is a prevailing method for detecting cracks in road surface images because of its detection ability. Previous research works focused on supervised convolutional neural networks (CNNs) without non-crack features or unsupervised crack analysis with limited accuracies. The novelty of this study is the addition of background classification. By increasing the number of non-crack categories, CNNs are driven to learn non-cra

To clarify the mechanism of hyperbilirubinemia in the setting of a left ventricular assist device (LVAD), the change in hepatocellular function, hepatic sinusoid endothelial microcirculation, and inflammatory response before and after LVAD implantation were evaluated. Eight consecutive patients underwent the placement of an LVAD, and serum levels of total bilirubin (TB), transaminases [alanine transaminase (ALT), aspartate transaminase (AST)], interleukin (IL-6, IL-8), and hyaluronic acid (HA),

Cardiopulmonary bypass (CPB) is known to induce an inflammatory response in association with neutrophil mediated lung injury. P-Selectin has been reported to be involved in the initiation of this inflammatory response by promoting the adhesion of neutrophils to endothelial cells in postcapillary venules. However, the role of P-selectin in the inflammatory response induced by CPB has never been clarified. To elucidate its role, we evaluated the effect of an anti-rat specific P-selectin monoclonal

The super-high-definition (SHD) movie distribution system described in this paper can transmit and display exceptionally high quality movies using an image container with 4096/spl times/2160 pixel resolution and 36-bit color. The total bit rate of an SHD movie to be shown at 24 frames per second is 7.6 Gbps, and should be compressed by 15:1 for transmission via Gigabit IP networks. The system is based on JPEG2000 coding technology. Coded streams of 500 Mbps can be continuously transmitted from t

In this paper, we present a digital holographic particle image velocimetry (DHPIV) technique with a spatio-temporal derivative method for velocity measurement in 3D space and the results of evaluating on its measurement accuracy. In this technique, hologram patterns are observed as digital images using an electronic camera, such as CCD or CMOS, and image reconstruction is carried out on a personal computer. Since an in-line observation system is utilized in conventional digital holography, a num