About
302
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Introduction
Dr. Jungpil Shin is a professor of School of Computer Science and Engineering, The University of AIZU and Supervisor of Pattern Processing Lab, The University of AIZU. He is serving to the University of AIZU as an academician since 1999.
His current research interests are pattern recognition, HCI (Human Computer Interaction), image processing, computer vision, and medical diagnosis. He is currently doing research on developing algorithms and systems for Non-Touch input interfaces to recognize and identify the Human and Gesture, Non-touch character input system based on hand tapping gestures, Gesture based non-touch flick character input system, automatic diagnosis and clinical evaluation of neurological movement disorders disease, lung disease prediction and diagnosis using advanced image
Publications
Publications (302)
In today’s world, there is a growing demand for potatoes that are produced professionally, successfully, and sustainably. This is due to changing climate conditions, worldwide population growth, and changing consumer demand. It is more crucial than ever to increase production capacity in order to satisfy future demand. However, insects and diseases...
Supply chain management relies on accurate backorder prediction for optimizing inventory control, reducing costs, and enhancing customer satisfaction. Traditional machine-learning models struggle with large-scale datasets and complex relationships. This research introduces a novel methodological framework for supply chain backorder prediction, addr...
In recent years, the combination of artificial intelligence (AI) and unmanned aerial vehicles (UAVs) has brought about advancements in various areas. This comprehensive analysis explores the changing landscape of AI-powered UAVs and friendly computing in their applications. It covers emerging trends, futuristic visions, and the inherent challenges...
Biomarkers associated with hepatocellular carcinoma (HCC) are of great importance to better understand biological response mechanisms to internal or external intervention. The study aimed to identify key candidate genes for HCC using machine learning (ML) and statistics-based bioinformatics models. Differentially expressed genes (DEGs) were identif...
The Metaverse, a transformative digital realm, holds immense promise for reshaping industries and human interactions while potentially addressing global challenges and democratizing opportunities. However, it also introduces a spectrum of complexities that demand careful navigation. To establish trustworthiness within the Metaverse ecosystem, gaini...
Innovation is the key to gaining a sustainable edge in an increasingly competitive global manufacturing landscape. For Bangladesh's manufacturing sector to survive and thrive in today's cutthroat business environment, adopting transformative technologies like the Internet of Things (IoT) is not a luxury but a necessity. This article tackles the for...
The development of deepfake technology, based on deep learning, has made it easier to create images of fake human faces that are indistinguishable from the real thing. Many deepfake methods and programs are publicly available and can be used maliciously, for example, by creating fake social media accounts with images of non-existent human faces. To...
Dynamic hand gesture recognition using a 3D
skeleton dataset has become the most attractive research
domain because of the multipurpose application. Although
many researchers have been working to develop hand gesture
systems, they are still facing challenges in achieving satisfactory
performance and more generalizable properties because of the
vari...
An ultra-wideband (UWB) slotted compact Vivaldi antenna with a microstrip line feed was evaluated for microwave imaging (MI) applications. The recommended FR4 substrate-based Vivaldi antenna is 50×50×1.5 mm3 in size. The proposed compact Vivaldi antenna showed good radiation characteristics and spanned an ultra-wide bandwidth of 10 GHz, ranging fro...
The movement of vehicles in and out of the predefined enclosure is an important security protocol that we encounter daily. Identification of vehicles is a very important factor for security surveillance. In a smart campus concept, thousands of vehicles access the campus every day, resulting in massive carbon emissions. Automated monitoring of both...
We investigated the relationship between the prefrontal cortex (PFC) and executive function during a drawing task. Thirty-three participants using pen tablets provided the data for this task. PFC activity was recorded using functional near-infrared spectroscopy (fNIRS) during a simple zig-zag task and a complex periodic line (PL) pattern task. For...
https://www.mdpi.com/journal/electronics/special_issues/VHOMM4O53F
In the modern digital world, patterns can be found in many facets of daily life. They can be physically observed or computationally detected using algorithms. In the digital environment, a pattern is represented by a vector or matrix feature value. Recently, numerous machine learni...
Recognition of Bengali handwritten digits has several unique challenges, including the variation in writing styles, the different shapes and sizes of digits, the varying levels of noise, and the distortion in the images. Despite significant improvements, there is still room for further improvement in the recognition rate. By building datasets and d...
The prevention of falls has become crucial in the modern healthcare domain and in society for improving ageing and supporting the daily activities of older people. Falling is mainly related to age and health problems such as muscle, cardiovascular, and locomotive syndrome weakness, etc. Among elderly people, the number of falls is increasing every...
This article intends to systematically identify and comparatively analyze state-of-the-art supply chain (SC) forecasting strategies and technologies. A novel framework has been proposed incorporating Big Data Analytics in SC Management (problem identification, data sources, exploratory data analysis, machine-learning model training, hyperparameter...
Variational quantum algorithms require many measurements to train parameters in their circuit to solve a given problem. If we need a highly accurate solution, the further number of measurements increases. However, the increase in the number of measurements may cancel out the usefulness of fast quantum computations. In this paper, we propose a metho...
Supply chain management relies on accurate backorder prediction for optimizing inventory control, reducing costs, and enhancing customer satisfaction. However, traditional machine-learning models struggle with large-scale datasets and complex relationships, hindering real-world data collection. This research introduces a novel methodological framew...
Supply chain management relies on accurate backorder prediction for optimizing inventory control, reducing costs, andenhancing customer satisfaction. Traditional machine-learning models struggle with large-scale datasets and complexrelationships. This research introduces a novel methodological framework for supply chain backorder prediction, addres...
Sign language recognition (SLR) aims to bridge speech-impaired and general communities by recognizing signs from given videos. However, due to the complex background, light illumination, and subject structures in videos, researchers still face challenges in developing effective SLR systems. Many researchers have recently sought to develop skeleton-...
The advancement of wireless communication technology is growing very fast. For next-generation communication systems (like 5G mobile services), wider bandwidth, high gain, and small-size antennas are very much needed. Moreover, it is expected that the next-generation mobile system will also support satellite technology. Therefore, this paper propos...
Sign Language Recognition (SLR) aims to bridge speech-impaired and general communities by recognizing signs from given videos. Researchers still face challenges developing efficient SLR systems because of the video’s complex background, light illumination, and subject structures. Recently many researchers developed a skeleton-based sign language re...
Citation: Hossain, M.M.; Hossain, M.A.; Musa Miah, A.S.; Okuyama, Y.; Tomioka, Y.; Shin, J. Stochastic Neighbor Embedding Feature-Based Hyperspectral Image Classification Using 3D Convolutional Neural Network. Electronics 2023, 12, 2082. Abstract: The ample amount of information from hyperspectral image (HSI) bands allows the non-destructive detect...
Skin cancer is a prevalent form of malignancy globally, and its early and accurate diagnosis is critical for patient survival. Clinical evaluation of skin lesions is essential, but it faces challenges such as long waiting times and subjective interpretations. Deep learning techniques have been developed to tackle these challenges and assist dermato...
Automatic recognition of human emotion has become an interesting topic among brain-computer interface (BCI) researchers. Emotion is one of the most fundamental features of a human subject. With proper analysis of emotion, the inner state of a human subject can be assessed directly. The human brain response can be competently represented by electroe...
The reliability of Underwater Wireless Sensor Networks (UWSNs) is measured in terms of energy consumption (EC), end-to-end delay(E2E) and packet delivery ratio (PDR). The adverse effects of channel may cause data loss. Reducing delay up to possible extend improves the reliability of the network, also increasing the number of nodes in a particular n...
Analyzing electroencephalography (EEG) signals with machine learning approaches has
become an attractive research domain for linking the brain to the outside world to establish communication in the name of the Brain-Computer Interface (BCI). Many researchers have been working on
developing successful motor imagery (MI)-based BCI systems. However, t...
Machine translation (MT) is the process of translating text
from one language to another using bilingual data sets and grammatical rules. Recent works in the field of MT have popularized sequence-to-sequence models leveraging neural attention and
deep learning. The success of neural attention models is yet to
be construed into a robust framework fo...
Attention deficit hyperactivity disorder (ADHD) is one of the major psychiatric and neurodevelopment disorders worldwide. Electroencephalography (EEG) signal-based approach is very important for the early detection and classification of children with ADHD. However, diagnosing children with ADHD using full EEG channels with all features may lead to...
Plant disease is a significant health concern among all living creatures. Early diagnosis can help farmers takenecessary steps to cure the disease and accelerate the production rate efficiently. Our research has beenconducted with five most common rice leaf diseases, such as bacterial leaf blight, brown spot, leaf blast,leaf scald, and narrow brown...
Oral health plays an important role in people’s quality of life as it is related to eating, talking, and smiling. In recent years, many studies have utilized artificial intelligence for oral health care. Many studies have been published on tooth identification or recognition of dental diseases using X-ray images, but studies with RGB images are rar...
Hepatocellular carcinoma (HCC) is the most common lethal malignancy of the liver worldwide. Thus, it is important to dig the key genes for uncovering the molecular mechanisms and to improve diagnostic and therapeutic options for HCC. This study aimed to encompass a set of statistical and machine learning computational approaches for identifying the...
Sign language recognition (SLR) is one of the crucial applications of the hand gesture recognition and computer vision research domain. There are many researchers who have been working to develop a hand gesture-based SLR application for English, Turkey, Arabic, and other sign languages. However, few studies have been conducted on Korean sign langua...
Air-writing is a modern human–computer interaction technology that allows participants to write words or letters with finger or hand movements in free space in a simple and intuitive manner. Air-writing recognition is a particular case of gesture recognition in which gestures can be matched to write characters and digits in the air. Air-written cha...
Campus or institution security has been a prominent area of study in recent decades. Facial identification, voice verification, and vehicle license plate recognition have all been used individually in the literature to prevent attackers from entering the facility. Although several academics have agreed that a hybrid recognition system may significa...
The definition of human-computer interaction (HCI) has changed in the current year because people are interested in their various ergonomic devices ways. Many researchers have been working to develop a hand gesture recognition system with a kinetic sensor-based dataset, but their performance accuracy is not satisfactory. In our work, we proposed a...
Diabetes is a long-term disease caused by the human body's inability to make enough insulin or to use it properly. This is one of the curses of the present world. Although it is not very severe in the initial stage, over time, it takes a deadly shape and gradually affects a variety of human organs, such as the heart, kidney, liver, eyes, and brain,...
The dynamic hand skeleton data have become increasingly attractive to widely studied for the recognition of hand gestures that contain 3D coordinates of hand joints. Many researchers have been working to develop skeleton-based hand gesture recognition systems using various discriminative spatial-temporal attention features by calculating the depend...
Diabetes is a long-term disease caused by the human body's inability to make enough insulin or to use it properly. This is one of the curses of the present world. Although it is not very severe in the initial stage, over time, it takes a deadly shape and gradually affects a variety of human organs, such as the heart, kidney, liver, eyes, and brain,...
Stroke is a dangerous medical disorder that occurs when blood flow to the brain is disrupted, resulting in neurological impairment. It is a big worldwide threat with serious health and economic implications. To solve this, researchers are developing automated stroke prediction algorithms, which would allow for early intervention and perhaps save li...
Falls represent a significant public health concern, particularly concerning vulnerable populations such as older adults. Accurate detection and classification of falls are critical for timely interventions that can prevent injuries and enhance the quality of life of these individuals. This work proposes a class ensemble approach based on convoluti...
Attention deficit hyperactivity disorder (ADHD) for children is one of the most common neurodevelopmental disorders and its prevalence has increased globally. Children with ADHD are faced with various difficulties, including inattention, impulsivity, and hyperactivity. Therefore, it is important to use an early detection system that is simple, non-...
Attention deficit hyperactivity disorder (ADHD) for children is one of the behavioral disorders that affect the brain’s ability to control attention, impulsivity, and hyperactivity and its prevalence has increased over time. The cure for ADHD is still unknown and only early detection can improve the quality of life for children with ADHD. At the sa...
Train incidents with animals and even humans have gotten more attention in the past. Every year, many animals are killed on train tracks, causing an imbalance of the ecosystem and significant delays in railway traffic. Similarly, sometimes train accident is prevalent at the rail gates, where motor vehicles are crossing the train line. All that happ...
The reliability of Underwater Wireless Sensor Networks (UWSNs) is measured in terms of energy consumption (EC), end-to-end delay(E2E), and packet delivery ratio (PDR). The adverse effects of a channel may cause data loss. Reducing delay up to the possible extent improves the reliability of the network, also increasing the number of nodes in a parti...
Osteoporosis, a common skeletal disorder, necessitates the identification of its risk factors to develop effective preventive measures. It is crucial to identify the underlying risk factors and their relationships with the response class attribute. Different machine learning (ML) algorithms and feature selection approaches are used to estimate the...
The name of individuals has a specific meaning and great significance. Individuals' names generally have substantial gender differences, and explicitly, Bengali names usually have a solid sexual identity. We can determine if a stranger is a man or a woman based on their name with remarkably suitable precision. In this research, we primarily conduct...
Electroencephalography (EEG) sensor plays an
important role in developing brain-computer interfaces (BCI) to
enhance human-computer interaction (HCI). Nowadays,
various types of research works are performed to develop EEG�based HCI systems for controlling and monitoring systems.
However, researchers are still facing challenges in developing
thi...
Gesture-based human-robot interaction has been an important area of research in recent years. The primary aspect for the researchers has always been to create a gesture detection system that is insensitive to lighting and backdrop surroundings. This research proposes a 3D gesture recognition and adaption system based on Kinect for human-robot inter...
An automated sleep stage categorization can readily face noise-contaminated EEG record-ings, just as other signal processing applications. Therefore, the denoising of the contaminated signalsis inevitable to ensure a reliable analysis of the EEG signals. In this research work, an empirical modedecomposition is used in combination with stacked autoe...
Writer identification has become a hot research topic in the fields of pattern recognition, forensic document analysis, the criminal justice system, etc. The goal of this research is to propose an efficient approach for writer identification based on online handwritten Kanji characters. We collected 47,520 samples from 33 people who wrote 72 online...
Music genre classification (MGC) is the process of putting genre labels on music by analyzing the sounds or words. With the rapid growth of music data repositories, MGC can be used in a lot of ways to organize and manage music recommendation systems, advertising, and streaming services. But there have been a lot of works on classifying English musi...
Non-touch-based keyboard became an urgent need in many situations where humans cannot directly touch the keyboard due to hygienic or security issues in human computer interaction. In this paper, a non-touch keyboard has been created using Leap Motion and Unity. The key layout is based on the qwerty type. There are five types of keyboards that we ha...
A gearbox is a critical rotating component that is used to transmit torque from one shaft to another. This paper presents a data-driven gearbox fault diagnosis system in which the issue of variable working conditions namely uneven speed and the load of the machinery is addressed. Moreover, a mechanism is suggested that how an improved feature extra...
Immunoglobulin-A-nephropathy (IgAN) is a kidney disease caused by the accumulation of IgAN deposits in the kidneys, which causes inflammation and damage to the kidney tissues. Various bioinformatics analysis-based approaches are widely used to predict novel candidate genes and pathways associated with IgAN. However, there is still some scope to cle...
Hand gestures are a common means of communication in daily life, and many attempts
have been made to recognize them automatically. Developing systems and algorithms to recognize
hand gestures is expected to enhance the experience of human–computer interfaces, especially when
there are difficulties in communicating vocally. A popular system for reco...
Communication between people with disabilities and people who do not understand sign language is a growing social need and can be a tedious task. One of the main functions of sign language is to communicate with each other through hand gestures. Recognition of hand gestures has become an important challenge for the recognition of sign language. The...
Fitness is important in people's lives. Good fitness habits can improve cardiopulmonary capacity, increase concentration, prevent obesity, and effectively reduce the risk of death. Home fitness does not require large equipment but uses dumbbells, yoga mats, and horizontal bars to complete fitness exercises and can effectively avoid contact with peo...
Network security is becoming a critical issue due to the spread of computer networks to ordinary people. User authentication is one of the most important part for network security. Although passwords are used in many personal computers, it has many well-known problems and it is antiquated. On the other hand, fingerprint or face based authentication...