지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 저널정보
- 한국정보통신학회 INTERNATIONAL CONFERENCE ON FUTURE INFORMATION & COMMUNICATION ENGINEERING 2019 INTERNATIONAL CONFERENCE ON FUTURE INFORMATION & COMMUNICATION ENGINEERING Vo.11 No.1
- 발행연도
- 2019.6
- 수록면
- 98 - 102 (5page)
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초록· 키워드
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Seamless and efficient diagnosis of pneumonia in children and adults is predominantly very important for the physicians. As pneumonia is a disease which kills around 50000 people each year globally therefore adequate treatment and adequate cure of the particular disease must be made essential for the prevention of the unnecessary deaths.
Conventionally for the detection and diagnosis of pneumonia physicians often use X-rays of chest to promptly and economically diagnose the disease The architecture of convolutional neural network devised in the work performs a thorough analysis on the chest x-rays by identifying the spatial placement of the activations that led to the detection of pneumonia in a chest x-ray. The model developed in the work posed an accuracy of 95.62% with an average precision and recall of 96% and 95% respectively.
Conventionally for the detection and diagnosis of pneumonia physicians often use X-rays of chest to promptly and economically diagnose the disease The architecture of convolutional neural network devised in the work performs a thorough analysis on the chest x-rays by identifying the spatial placement of the activations that led to the detection of pneumonia in a chest x-ray. The model developed in the work posed an accuracy of 95.62% with an average precision and recall of 96% and 95% respectively.
목차
Abstract
I. INTRODUCTION
II. RELATED WORK
III. METHODS AND RESULTS
IV. CONCLUSION
REFERENCES
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UCI(KEPA) : I410-ECN-0101-2019-004-000919845