A5103055066- EEG and Brain-Computer Interfaces
- Artificial Intelligence in Healthcare and Education
- Machine Learning in Healthcare
- AI in cancer detection
- Advanced Vision and Imaging
- Water Quality Monitoring Technologies
- IoT and GPS-based Vehicle Safety Systems
- Advanced Image Processing Techniques
- Brain Tumor Detection and Classification
- Industrial Vision Systems and Defect Detection
- COVID-19 diagnosis using AI
- Advanced Neural Network Applications
- Textile materials and evaluations
- Explainable Artificial Intelligence (XAI)
- Image and Signal Denoising Methods
- Optical measurement and interference techniques
- Neural dynamics and brain function
- Blind Source Separation Techniques
- Innovation in Digital Healthcare Systems
- Artificial Intelligence in Healthcare
University of Technology Sydney
2024
Hongik University
2022-2023
Artificial intelligence (AI)-based telemedicine systems for early Alzheimer's detection using low-cost modalities are vital rural or underdeveloped areas where travelling distance and high-cost devices like MRI drawbacks. These require eXplainable AI (XAI) reliable outcomes intuitive explanations. Current XAI evaluations lack input from medical professionals overlook stakeholder diversity, leading to potential biases. This project aims develop a cost-effective system, enhance AD in areas,...
Can ChatGPT diagnose Alzheimer's Disease (AD)? AD is a devastating neurodegenerative condition that affects approximately 1 in 9 individuals aged 65 and older, profoundly impairing memory cognitive function. This paper utilises 9300 electronic health records (EHRs) with data from Magnetic Resonance Imaging (MRI) tests to address an intriguing question: As general-purpose task solver, can accurately detect using EHRs? We present in-depth evaluation of black-box approach zero-shot multi-shot...
There is a great range of spectacular coral reefs in the ocean world. Unfortunately, they are jeopardy, due to an overabundance one specific starfish called coral-eating crown-of-thorns (or COTS). This article provides research deliver innovation COTS control. Using deep learning model based on You Only Look Once version 5 (YOLOv5) algorithm embedded device for detection. It aids professionals optimizing their time, resources and enhancing efficiency preservation all around As result,...
Defective stitch inspection is an essential part of garment manufacturing quality assurance. Traditional mechanical defect detection systems are effective, but they usually customized with handcrafted features that must be operated by a human. Deep learning approaches have recently demonstrated exceptional performance in wide range computer vision applications. The requirement for precise detail evaluation, combined the small size patterns, undoubtedly increases difficulty identification....
State-space models (SSMs) have garnered attention for effectively processing long data sequences, reducing the need to segment time series into shorter intervals model training and inference. Traditionally, SSMs capture only temporal dynamics of data, omitting equally critical spectral features. This study introduces EEG-SSM, a novel state-space model-based approach dementia classification using EEG data. Our features two primary innovations: EEG-SSM components. The component is designed...
With the advancement of deep learning, single-image super-resolution (SISR) has made significant strides. However, most current SISR methods are challenging to employ in real-world applications because they doubtlessly employed by substantial computational and memory costs caused complex operations. Furthermore, an efficient dataset is a key factor for bettering model training. The hybrid models CNN Vision Transformer can be more task. Nevertheless, require or extremely high-quality datasets...
최근 팬데믹(Pandemic)으로 인하여 감염병 예방을 위하여 여러 연구가 시도되고 있다. 밀폐된 공간에 얼마나 많은 인원이 오고 가는 지에 대한 통계적 데이터는 위한 매우 중요한 척도이다. 이에 따라 특정한 공간에서 유동인구를 세는 기술인 피플 카운팅(People Counting)을 이용한 카운터(People Counter)의 수요가 늘게 되었다. 본 논문에서는 딥러닝을 객체 추적 모델로 임베디드 기기에서도 실시간으로 작동 가능한 카운터 개발을 연구 목적으로 한다. 모델은 감지 모델과 Deep SORT 알고리즘을 결합하였고, 계산 속도가 빨라 환경에 적합한 경량화된 SSD MobileNet V2를 사용하였다. 개발된 카운터는 출입구 주변 객체를 추적하며 카운팅하고, 실시간 동작이 가능함을 확인하였다.