A5045398581- Radiomics and Machine Learning in Medical Imaging
- Human Pose and Action Recognition
- Sports and Physical Education Research
- Machine Learning in Healthcare
- Artificial Intelligence in Healthcare and Education
- Colorectal Cancer Screening and Detection
- Pharmacovigilance and Adverse Drug Reactions
- Anomaly Detection Techniques and Applications
- Industrial Vision Systems and Defect Detection
- Digital Media Forensic Detection
- Neural Networks and Applications
- Handwritten Text Recognition Techniques
- Multimodal Machine Learning Applications
- Advanced Neural Network Applications
- Machine Learning and Data Classification
- Sports Dynamics and Biomechanics
- Stroke Rehabilitation and Recovery
- Neural Networks and Reservoir Computing
- Biometric Identification and Security
- Advanced Image and Video Retrieval Techniques
- Biosimilars and Bioanalytical Methods
- Human Motion and Animation
- Diversity and Impact of Dance
- Advanced Steganography and Watermarking Techniques
- Currency Recognition and Detection
Hansung University
2019-2025
To address the challenges associated with fuel consumption in vehicles low efficiency, several factors must be recognized. Identifying key of efficiency prediction is crucial for making accurate decisions. Therefore, we propose a comprehensive framework that uses machine learning to predict by integrating various vehicle information. The proposed method comprises predictive model and analysis utilizing attributes, such as type, engine displacement, grade, enhance accuracy. We conducted...
Background: The large language model (LLM) has the potential to be applied clinical practice. However, there been scarce study on this in field of gastroenterology. Aim: This explores utility two LLMs gastroenterology: a customized GPT and conventional GPT-4o, an advanced LLM capable retrieval-augmented generation (RAG). Method: We established with BM25 algorithm using Open AI’s GPT-4o model, which allows it produce responses context specific documents including textbooks internal medicine...
Image captioning is a task to generate new caption using the training data of image and caption. Since existing deep learning black-box model, it crucial analyze influence on each module for understanding model. In this paper, we impact five modules do comparative analysis according three losses two optimizations datasets. From extensive experiments, best component has been identified as an improved method.
<sec> <title>BACKGROUND</title> As health care continues to evolve with technological advancements, the integration of artificial intelligence into clinical practices has shown promising potential enhance patient and operational efficiency. Among forefront these innovations are large language models (LLMs), a subset designed understand, generate, interact human at an unprecedented scale. </sec> <title>OBJECTIVE</title> This systematic review describes role LLMs in improving diagnostic...
When deep learning models classify the actual data and outlier data, most of them do not have enough information about outlier, which might cause misclassification. Therefore, there is a need for an efficient way to analyze through visualization. We propose visualization method combining LBP, LLE SMOTE detection. Furthermore, we introduce new confusion that uses similarity pixel density distributions. also present histogram using frequency position's distribution in EDA. To validate its...