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초록
In this study, we propose a novel approach for rapid and accurate pathogen detection by integrating Polydiacetylene (PDA) hydrogel sensors with advanced deep learning algorithms and visualization techniques. PDA hydrogel sensors exhibit a color transition in the presence of pathogens, enabling straightforward and quick pathogen detection. We developed a reliable pathogen detection system that combines deep neural network algorithms with color quantification technology for image-based analysis. This image-based system retains the ease of pathogen detection offered by PDA sensors while deriving quantified color standards to overcome the limitations of human visual assessment, enhancing reliability. This advancement contributes to public health and the development and application of pathogen detection technology.
키워드
- 제목
- 병원균 검출용 PDA 색 전이 센서 분석을 위한 심층신경망 기술
- 제목 (타언어)
- Deep Neural Network Technology for Analyzing PDA Colorimetric Transition Sensors in Pathogen Detection
- 저자
- 전준현; 장희수; 신민경; 전태준; 김선민
- 발행일
- 2024-07
- 유형
- Y
- 저널명
- 한국가시화정보학회지
- 권
- 22
- 호
- 2
- 페이지
- 27 ~ 34