Joon Huang Chuah

Southern University College

Ensuring efficient grading of guavas is crucial for timely postharvest storage and maximizing profits. Currently, the subjective nature of manual grading underscores the need for more sophisticated methodologies. However, employing machine vision for intelligent grading faces hurdles due to the diverse characteristics of guavas and the high develop...

Image shadow removal is a typical low-level vision problem, where the presence of shadows leads to abrupt changes in brightness in certain regions, affecting the accuracy of upstream tasks. Current shadow removal methods still face challenges such as residual boundary artifacts, and capturing feature information at shadow boundaries is crucial for...

Lower back pain is one of the most prevalent health issues, affecting more than 80% of adults worldwide. Thermotherapy including heat wrap and dry sauna has long been utilized for pain relief and relaxation. Far-infrared graphene-based thermography is a heat therapy method where the graphene emits far-infrared rays that can penetrate human skin. Ho...

Continual Learning represents a significant challenge within the field of computer vision, primarily due to the issue of catastrophic forgetting that arises with sequential learning tasks. Among the array of strategies explored in current continual learning research, replay-based methods have shown notable effectiveness. In this paper, we introduce...

Efficient grading of mangosteens is vital in ensuring timely post-harvest storage and preservation for maximizing profits. Currently, manual grading is susceptible to subjective biases, thereby warranting a more intelligent grading approach. Innovative solutions for automated fruit grading have been developed based on computer vision. However, inte...

Zirconium oxide is a promising dielectric material for electronic applications due to favorable properties such as large band gap and high dielectric constant. It is compatible with solution processing, which can be a useful alternative method of dielectric deposition for low-cost applications while maintaining sufficiently good quality. The effect...

Digitalization is revolutionizing our way of life and catalyzing the transformation into smart city. Intelligent Transportation System (ITS) being an indispensable component of smart city leverages massive amount of collected information to improve traffic efficiency, thereby creating a safer and comfortable commuting environment for the users. One...

The fault diagnosis of rolling bearing is of great significance in industrial safety. The method of infrared thermal image combined with neural network can diagnose the fault of rolling bearing in a non-contact manner, however its data in different scenes are often unbalanced and difficult to obtain. In this paper, an unsupervised learning framewor...

Pap smear testing is crucial for early diagnosis of cervical cancer, but cell overlapping poses a significant challenge to diagnostic accuracy, as improper processing of overlapping cells can lead to misclassification. While significant research efforts have been devoted to segmenting overlapping cells, there is an absence of thorough reviews cover...

Source-Free Domain Adaptation (SFDA) is an important reseach topic in domains with data privacy concerns. Existing SFDA studies have successfully achieved domain adaptation without revealing source domain data, significantly reducing the possibility of privacy leaks. However, complete SFDA (cSFDA), which does not disclose even the source domain m...

Enhancing video recognition systems with advanced abnormal behavior recognition technologies is crucial for school safety and campus security. Traditional methods primarily rely on visual data and often fail to recognize complex behaviors due to intricate backgrounds. Similarly, traditional audio processing techniques struggle to capture transient...

Background: The scientific revolution in the treatment of many illnesses has been significantly aided by stem cells. This paper presents an optimal control on a mathematical model of chemotherapy and stem cell therapy for cancer treatment. Objective: To develop effective hybrid techniques that combine the optimal control theory (OCT) with the ev...

Worldwide, cardiovascular disease is the leading cause of death. Based on clinical data, a Machine Learning (ML) system can detect cardiac disease in its early stages, which enables a reduction in mortality rates. However, imbalanced and high dimensionality data have been a persistent challenge in ML, impeding accurate predictive data analysis in m...

Given ever-increasing private transportation ownership, a rising population, and unceasing mobility, it is crucial to ensure the usage and improvement of public transportation services. Therefore, it is important to review and understand relationships between variables affecting ridership to boost them. This paper acts as a preliminary data analysi...

Passive human activity recognition without requiring a device is crucial in various fields, including smart homes, health care, and identification. However, current systems for human activity recognition require a dedicated device, or they need to be more suitable for scenarios where signals are transmitted through walls. To address this challenge,...

Oil palm is a key agricultural resource in Malaysia. However, palm disease, most prominently basal stem rot caused at least RM 255 million of annual economic loss. Basal stem rot is caused by a fungus known as Ganoderma boninense . An infected tree shows few symptoms during early stage of infection, while potentially suffers an 80% lifetime yield l...

Social media platforms such as Twitter and Facebook have become popular channels for people to record and express their feelings, opinions, and feedback in the last decades. With proper extraction techniques such as sentiment analysis, this information is useful in many aspects, including product marketing, behavior analysis, and pandemic managemen...

Alzheimer's disease (AD) is a neurodegenerative disorder that causes memory degradation and cognitive function impairment in elderly people. The irreversible and devastating cognitive decline brings large burdens on patients and society. So far, there is no effective treatment that can cure AD, but the process of early-stage AD can slow down. Early...

Cardiac health diseases are one of the key causes of death around the globe. The number of heart patients has considerably increased during the pandemic. Therefore, it is crucial to assess and analyze the medical and cardiac images. Deep learning architectures, specifically convolutional neural networks have profoundly become the primary choice for...

Tool wear in CNC milling is a gradual process which significantly affects product quality. Left unmonitored, it could increase risks of tool breakage, leading to losses due to scrap and equipment damage. A modular neural network (MNN), the dissociation artificial neural network (Dis-ANN), was proposed in this paper for tool wear prediction. The Dis...

The segmentation of the left ventricle (LV) is one of the fundamental procedures that must be performed to obtain quantitative measures of the heart, such as its volume, area, and ejection fraction. In clinical practice, the delineation of LV is still often conducted semi-automatically, leaving it open to operator subjectivity. The automatic LV seg...

Video anomaly detection aims to identify anomalous segments in a video. It is typically trained with weakly supervised video-level labels. This paper focuses on two crucial factors affecting the performance of video anomaly detection models. First, we explore how to capture the local and global temporal dependencies more effectively. Previous archi...

The intelligent campus surveillance system is beneficial to improve safety in school. Abnormal behavior recognition, a field of action recognition in computer vision, plays an essential role in intelligent surveillance systems. Computer vision has been actively applied to action recognition systems based on Convolutional Neural Networks (CNNs). How...

Palm oil industry is an important economic resource for Malaysia. However, an oil palm tree disease called Basal Stem Rot has impeded the production of palm oil, which caused significant economic loss at the same time. The oil palm tree disease is caused by a fungus known as Ganoderma Boninense . Infected trees often have little to no symptoms du...

Vehicle Make and Model Recognition (VMMR) is one of the fundamental elements in Intelligent Transportation System (ITS) that becomes the enabler for plenty of downstream tasks. Most of the past studies advance the recognition performance by focusing on the top-level feature maps but this practice hinders the ability of the network to learn features...

Vehicle Type Recognition (VTR) is a significant segment within the vehicle recognition field. It provides an alternative identification method aside from license plate recognition and vehicle make and model recognition. Most of the recent studies use Convolutional Neural Networks (CNNs) to perform VTR. However, the feature responses obtained from C...

A mathematical model of cancer chemotherapy is considered as an optimal control problem with the objective of either minimizing a weighted sum of tumor cells and drug dosage or the terminal tumor volume. The control process is subject to three state constraints involving an upper bound on drug toxicity, a lower bound on the white blood cells (WBCs)...

One of the emerging and powerful tools of Artificial Intelligence (AI) in computer vision is Convolutional Neural Network (CNN) which can outperform traditional algorithms for crack detection by extracting unique image features. The segmentation of crack images is intensively affected by the imbalanced presence of crack and non-crack elements. Tack...

One of the primary factors contributing to death across all age groups is cardiovascular disease. In the analysis of heart function, analyzing the left ventricle (LV) from 2D echocardiographic images is a common medical procedure for heart patients. Consistent and accurate segmentation of the LV exerts significant impact on the understanding of the...

Optic neuritis is an acute inflammation of myelin sheath that damages optic nerve while Magnetic Resonance Imaging (MRI) is one of the non-invasive alternatives to diagnose optic neuritis by measuring the mean cross-sectional area of the optic nerve. However, the extraction and analysis of optic nerve with MRI are challenging due to its discrete di...

Environment perception is the premise for intelligent vehicles to drive safely and stably. Despite the rapid development of road detection technology based on visual images, it is still challenging to robustly identify road areas in visual images due to the influence of illumination changes and noise. In order to solve this problem, we introduce a...

Driver distraction is one of the main causes of fatal traffic accidents. Therefore, the ability to detect driver inattention is essential in building a safe yet intelligent transportation system. Currently, the available driver distraction detection systems are not widely available or limited to specific class actions. Various research efforts have...

Intraoperative neuromonitoring (IONM) has been used to help monitor the integrity of the nervous system during spine surgery. Transcranial motor-evoked potential (TcMEP) has been used lately for lower lumbar surgery to prevent nerve root injuries and also to predict positive functional outcomes of patients. There were a number of studies that prove...

In the late December of 2019, a novel coronavirus was discovered in Wuhan, China. In March 2020, WHO announced this epidemic had become a global pandemic and that the novel coronavirus may be mild to most people. However, some people may experience a severe illness that results in hospitalization or maybe death. COVID-19 classification remains chal...

Agriculture is an important regional economic industry in Asian regions. Ensuring food security and stabilizing the food supply are a priority. In response to the frequent occurrence of natural disasters caused by global warming in recent years, the Agriculture and Food Agency (AFA) in Taiwan has conducted agricultural and food surveys to address t...

Transcranial motor evoked potential (TcMEP) is one of the modalities in intraoperative neuromonitoring (IONM) which has been used in spine surgeries to prevent motor function injuries. Studies have shown that improvement to TcMEP could be a potential prognostic information on the actual improvement to the patient after surgery. There is no objectiv...

Walking speed is a powerful predictor of health events which are related to musculoskeletal disorder and mental disease. One of the established computerized technique which employed to perform the gait analysis is motion analysis system. This system allows researchers to perform quantification or estimation on human pose and body shape from multipl...

The Internet of Things (IoT) technology has revolutionized the healthcare industry by enabling a new paradigm for healthcare delivery. This paradigm is known as the Internet of Medical Things (IoMT). IoMT devices are typically connected via a wide range of wireless communication technologies, such as Bluetooth, radio-frequency identification (RFID)...

Walking speed provides a good proxy for gait abnormalities as individuals with medical morbidities tend to walk slower than healthy subjects. The walking speed assessment can be utilized as a powerful predictor of health events, which are related to musculoskeletal disorder and mental disease. The expanding need to distinguish gait pattern of indiv...

Deep learning based image classification systems require large amount of training data and long training time. However, the availability of large annotated image dataset is usually limited and expensive to generate, which limits a vision system to adapt to new task efficiently. In this paper, a few-shot classification framework is proposed which ca...

Recent research that applies Transformer-based architectures to image captioning has resulted in state-of-the-art image captioning performance, capitalising on the success of Transformers on natural language tasks. Unfortunately, though these models work well, one major flaw is their large model sizes. To this end, we present three parameter reduct...

Recent research that applies Transformer-based architectures to image captioning has resulted in state-of-the-art image captioning performance, capitalising on the success of Transformers on natural language tasks. Unfortunately, though these models work well, one major flaw is their large model sizes. To this end, we present three parameter reduct...

Image noise is a variation of uneven pixel values that occurs randomly. A good estimation of image noise parameters is crucial in image noise modeling, image denoising, and image quality assessment. To the best of our knowledge, there is no single estimator that can predict all noise parameters for multiple noise types. The first contribution of ou...

Convolutional Neural Networks (CNN) have immense potential to solve a broad range of computer vision problems. It has achieved encouraging results in numerous applications of engineering, medical, and other research fields due to the advancement in hardware, data collection procedures, and efficient algorithms. These innovations have changed the wa...

Coronavirus of 2019 is an ongoing pandemic that has infected millions of people and costed the life of more than three million people. It is a highly transmitting disease that has exhausted all the healthcare facilities trying to contain its spread. It has exposed the need for more health facilities and experts to cope with this pandemic without im...

Readmission manifests signs of degraded quality of care and increased healthcare cost. Such adverse event may be attributed to premature discharge, unsuccessful treatments, or worsening comorbidities. Predictive modeling provides useful information to identify patients at a higher risk for readmission for targeted interventions. Though many studies...

Heart disease is the leading cause of death worldwide. A Machine Learning (ML) system can detect heart disease in the early stages to mitigate mortality rates based on clinical data. However, the class imbalance and high dimensionality issues have been a persistent challenge in ML, preventing accurate predictive data analysis in many real-world app...

Cardiovascular disease (CVD) is the leading cause of death worldwide. A Machine Learning (ML) system can predict CVD in the early stages to mitigate mortality rates based on clinical data. Recently, many research works utilized different machine learning approaches to detect CVD or identify the patient’s severity level. Although these works obtaine...

Human motion analysis is fundamental in many real applications such as surveillance and monitoring, human-machine interface, medical motion analysis and diagnosis. With the increasing amount of data in biomechanics research, it is becoming increasingly important to automatically analyse and understand object motions from large amount of footage and...

Driver distraction is the main factor of severe traffic accidents and has become an essential issue in the traffic safety field. Hence, driver inattention systems are crucial in ensuring the safety of road users. With the introduction of Vision Transformer for computer vision tasks, there is a lack of comprehensive evaluation of various models for...

Spine surgeries impose risk to the spine’s surrounding anatomical and physiological structures especially the spinal cord and the nerve roots. Intraoperative neuromonitoring (IONM) is a technology developed to monitor the integrity of the spinal cord and the nerve roots via the surgery. Transcranial motor evoked potential (TcMEP) (one of the IONM m...

Object detection in aerial images has been an active research area thanks to the vast availability of unmanned aerial vehicles (UAVs). Along with the increase of computational power, deep learning algorithms are commonly used for object detection tasks. However, aerial images have large variations, and the object sizes are usually small, rendering...

With the advancement of deep models, research work on image captioning has led to a remarkable gain in raw performance over the last decade, along with increasing model complexity and computational cost. However, surprisingly works on compression of deep networks for image captioning task has received little to no attention. For the first time in i...

With the advancement of deep models, research work on image captioning has led to a remarkable gain in raw performance over the last decade, along with increasing model complexity and computational cost. However, surprisingly works on compression of deep networks for image captioning task has received little to no attention. For the first time in i...

Neural networks have become deeper in recent years and this has improved its capacity to handle more complex tasks. However, deep neural network has more parameters and is easier to overfit, especially when training samples are insufficient. In this paper, we present a new regularization technique called batch contrastive regularization to improve...