Jun Kang Chow

• Doctor of Philosophy
• PostDoc Position at Hong Kong University of Science and Technology

This paper reports the application of deep learning for implementing the anomaly detection of defects on concrete structures, so as to facilitate the visual inspection of civil infrastructure. A convolutional autoencoder was trained as a reconstruction-based model, with the defect-free images, to rapidly and reliably detect defects from the large v...

Inspection of civil infrastructure is a major challenge to engineers due to the limitations in existing practice, which are as laborious, time-consuming and prone to error. To address these issues, we have applied deep learning for image-based inspection of concrete defects of civil infrastructure, and have established an artificial intelligence-em...

This paper reports a feasible alternative to compile a landslide inventory map (LIM) from remote sensing datasets using the application of an artificial intelligence–driven methodology. A deep convolutional neural network model, called LanDCNN, was developed to generate segmentation maps of landslides, and its performance was compared with the benc...

This paper presents a framework for automated defect inspection of the concrete structures, made up of data collection, defect detection, scene reconstruction, defect assessment and data integration stages. A mobile data collection system, comprising a 360° camera and a digital Light Detection and Ranging (LiDAR), is developed to render high flexib...

Training a deep learning model is always challenging as the data annotation requires expert knowledge, and is time consuming and laborious. To address this issue, the authors formulate an active learning framework to facilitate the training of deep learning models for performing concrete crack segmentation from images. The Monte Carlo dropout (MCDO...

Two research studies have been implemented to explore the potential of applying artificial intelligence (AI) technologies in works projects and maintenance work of the Drainage Services Department (DSD) for enhancing the efficiency related to environmental monitoring and structural inspection, referred to as the AIEIA and AIBIM projects, respective...

This paper reports the innovative development of a flexible, multiple-layer, economical but robust, and automated high-speed shear wave (Vs) tomographic control and data acquisition system for process monitoring in the laboratory and the associated validation for monitoring the dynamic process of model pile installation. This tailor-made tomographi...

This paper reports the use of the deep learning-based technique to characterize the particle orientation of clay samples. The U-Net model was applied to perform semantic segmentation for identifying individual kaolinite particles, based on the scanning electron microscopic images taken from clay samples subjected to 1-D consolidation. The measurabl...

Drainage network extraction is essential for different research and applications. However, traditional methods have low efficiency, low accuracy for flat regions, and difficulties in detecting channel heads. Although deep learning techniques have been used to solve these problems, different challenges remain unsolved. Therefore, we introduced distr...

Automatic bird detection in ornithological analyses is limited by the accuracy of existing models, due to the lack of training data and the difficulties in extracting the fine-grained features required to distinguish bird species. Here we apply the domain randomization strategy to enhance the accuracy of the deep learning models in bird detection....

In this study, the U-oedometer, a novel modified oedometer cell equipped with tailor-made needle probes, is developed to easily and accurately measure the excess pore water pressure (\(\Delta u\)) during 1D consolidation tests and to determine the coefficient of consolidation (\(c_{\text{v}}\)). The 3D printing technique is applied to make simple y...

This study reports model pile tests designed to characterize the underlying mechanisms of driven pile setup in dry sand by means of stress measurement with the tactile pressure sensors and spatio-temporal, shear-wave velocity (Vs) distributions using an automated high-speed tomographic imaging system. The pile-load test results demonstrate a distin...

Discriminator from generative adversarial nets (GAN) has been used by some research as feature extractor in transfer learning and worked well. But there are also some studies believed that this is a wrong research direction because intuitively the task of discriminator focuses on separating the real samples from the generated ones, making the featu...

This paper describes a microstructural characterizations of high-quality, load-preserved fabric 1-D consolidated kaolinite samples, which covers from the beginning stage of clay sample preparation to the final stage of the microstructural analyses. To achieve this goal, a tailor-made oedometer is produced using the 3-D printing technique. First, a...

This paper reports the density effect on the aging-induced increase in soil stiffness based on discrete-element method (DEM) simulations conducted on dense, medium-dense, and loose samples for the study. Like experimental observations, among the three investigated, the medium-dense sample showed the highest aging rate in terms of the increase in th...

In this paper, through micromechanical analyses, the microstructural responses of kaolinite samples subjected to 1-D consolidation were quantitatively analyzed. Using a tailor-made, 3D-printed oedometer in preparing samples subjected to different loading levels, the applied loading was maintained during the freezing process of the sample in order t...

In this study, a novel method for pore network extraction in the weakly consolidated media is reported, which unifies both the Delaunay tessellation (DT) and maximal ball (MB) methods in a complementary way. This unified method retains the advantages of both methods, and most importantly, eliminates the disadvantages when either the DT or the MB me...

In this study, the economical FlexiForce sensor, which is thin and flexible, was used to measure Ko and the excess pore water pressure during a 1D consolidation test on kaolinite clay samples. Before the sensor could be used in the measurement, a special waterproof coating was applied, after which sensor calibration was carried out. The coated Flex...

In this paper, the responses of kaolinite samples with two different soil structures, i.e., unwashed and pH 7.8 samples, under 1-D consolidation, isotropic loading–unloading and triaxial shearing are examined. The focus is on the associated changes in the pore-size distribution. During isotropic consolidation, the unwashed sample, with an open, agg...