Identifying the writer of handwritten text poses a significant challenge due to the diversity and variability inherent in handwriting styles. This paper proposes a novel approach based on Siamese neural network (SNN) for the task of writer identification in Khmer handwriting. The SNN architecture was leveraged for training and testing on a dataset specifically collected for this purpose. The dataset comprised 1400 samples collected from students
As artificial intelligence has grown, a large language model is a model train with a vast quantity of textual data. This model can be tailored to a particular task, such as chatbots, text production, and question-answering. However, most of the existing pre-trained models nowadays were trained with English datasets, leading to limited support and low performance in other languages, especially low-resource languages like Khmer. To address the imba
Artificial intelligence, fueled by machine learning and deep learning techniques, is revolutionizing various domains. Reinforcement learning (RL) stands out as a potent method for training agents to navigate complex environments and make informed decisions. Our focus is on applying RL techniques, specifically Convolutional Neural Networks (CNNs) combined with policy gradient methods, to enhance the gameplay experience of Khmer chess. Our goal is
Word spotting plays a crucial role in document analysis, particularly for ancient palm leaf manuscripts. Khmer palm leaf manuscripts, which are written on rectangularly cut and dried palm leaf sheets, hold significant cultural value in Cambodia. These manuscripts contain valuable historical, religious, and linguistic information, making their preservation essential. However, extracting information from them is challenging due to their fragility,
This research focuses on preserving Cambodia's historical Khmer palm leaf manuscripts by proposing a text-image reconstruction and reparation framework using advanced computer vision and deep learning techniques. To address the preservation, Convolutional Neural Networks (CNN) and Generative Adversarial Networks (GAN) are employed to fill in the missing patterns of characters in the damaged images. The study utilizes the SleukRith Set [1], which
With the growth of usage of Docker containers in the recent year, Vulnerability scanning is essential to scanning and detecting known flaws and vulnerabilities in that specific Docker image. Using a custom docker image with third-party libraries in our code base authenticity or knowing their flaws can cause a lot of trouble in the future. In this case, vulnerability scanning tools such as Clair, Trivy, Anchor Grype, and Snyk are used for detectin
Non-intrusive load monitoring systems (NILM) have attracted much attention due to their potential contribution to energy savings for individual households. The approach analyzes the load consumption of each device in terms of the total energy consumption of the house. The selection of essential load signatures for load identification expresses a crucial challenge with NILM techniques. Several studies that have been proposed in the literature clai
Crop diseases, unfavorable growth, and nutritional deficiencies have a significant impact on the quality and quantity of agricultural income. According to the United Nations’ Food and Agriculture Organization, it is estimated that pre- and post-harvest diseases alone destroy at least 20–40% of global agricultural production. In developing countries like Cambodia, farmers tend to have a limited understanding of crop diseases and how to treat them,
In the chain of the healthcare domain even in the public or private sector of a developing country, there is still much concern about information sharing, security, and privacy, especially for identity management. In Cambodia, currently, the centralized framework for identity management is mostly used, which highly depends on a single trust third-party Certificate Authority (CA) such as the General Department of ICT (GDICT) at the Ministry of Pos
Nowadays, smart home technology has become one of the leading IoT-based projects and as a result of that there are lots of new IoT-based products available in society that allow people to live more convenient and secure lives at home. Many people are aware of this technology, and the smart home application helps people to manage their schedules, home lighting, electricity bills, grocery lists, and also their home security. Today, face recognition
