초분광 영상을 위한 3-D 콘볼루션 네트워크 : 영상복원부터 영상분류까지

유미 2020년

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논문상세정보

- 저자 유미
- 기타서명 3-D 콘볼루션 네트워크
- 형태사항 삽화, 표: xiv, 165 p.: 26 cm
- 일반주기 지도교수: 이준환, 전북대학교 논문은 저작권에 의해 보호받습니다, 참고문헌 : p. 147-162
- 학위논문사항 학위논문(박사)-, 전자·정보공학부(컴퓨터공학 전공), 2020. 2, 전북대학교 일반대학원
- 발행지 전주
- 언어 eng
- 출판년 2020
- 발행사항 전북대학교 일반대학원
- 주제어 3-D convolutional neural network 3D 컨볼 루션 신경망 classification denoising generative adversarial network hyperspectral image residual learning super resolution synthesis 노이즈제거 분류 생성 적대적 네트워크 잔차 학습 초분광 이미지 초해상도 합성
- 참고문헌( 177)
유사주제 논문( 913)

인용/피인용

초분광 영상을 위한 3-D 콘볼루션 네트워크 : 영상복 ...

' 초분광 영상을 위한 3-D 콘볼루션 네트워크 : 영상복원부터 영상분류까지' 의 주제별 논문영향력

논문영향력 요약
동일주제 총논문수	논문피인용 총횟수	주제별 논문영향력의 평균
주제	3-D convolutional neural network 3D 컨볼 루션 신경망 classification denoising generative adversarial network hyperspectral image residual learning super resolution synthesis 노이즈제거 분류 생성 적대적 네트워크 잔차 학습 초분광 이미지 초해상도 합성
927	0	0.0%

논문영향력
주제		주제별 논문수	주제별 논문영향력
주제어	3-D convolutional neural netw ...	2	0.0%
	3D 컨볼 루션 신경망	2	0.0%
	classification	228	0.0%
	denoising	26	0.0%
	generative adversarial networ ...	34	0.0%
	hyperspectral image	18	0.0%
	residual learning	6	0.0%
	super resolution	50	0.0%
	synthesis	124	0.0%
	노이즈제거	10	0.0%
	분류	350	0.0%
	생성 적대적 네트워크	1	0.0%
	잔차 학습	6	0.0%
	초분광 이미지	4	0.0%
	초해상도	12	0.0%
	합성	56	0.0%
계		929	0.0%
* 다른 주제어 보유 논문에서 피인용된 횟수

' 초분광 영상을 위한 3-D 콘볼루션 네트워크 : 영상복원부터 영상분류까지' 의 참고문헌

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초분광 영상을 위한 3-D 콘볼루션 네트워크 : 영상복원부터 영상분류까지

유사주제 논문( 913)

' 초분광 영상을 위한 3-D 콘볼루션 네트워크 : 영상복원부터 영상분류까지' 의 주제별 논문영향력

주제별 논문영향력

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