Papers with Code 아카이브
Image Enhancement
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 10
- 평가표
- 7
- 보존된 평가 기록
- 26
Image Enhancement is basically improving the interpretability or perception of information in images for human viewers and providing ‘better’ input for other automated image processing techniques. The principal objective of Image Enhancement is to modify attributes of an image to make it more suitable for a given task and a specific observer.
Source: A Comprehensive Review of Image Enhancement Techniques
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/yuqj1990/deepano_face_train
https://github.com/yuqj1990/deepano_train
https://github.com/yuqj1990/face_train
https://github.com/zhangyhuaee/KinD
https://github.com/zhenngbolun/Learnbale_Bandpass_Filter
https://github.com/zhenqifu/pairlie
https://github.com/zhreshold/mxnet-ssd
https://github.com/zhucheng725/MobileNetv1_Segnet_keras_tensorrt
https://github.com/zhuyi55/week9
https://github.com/zjZSTU/SSD
https://github.com/zoeyuchao/caffe-ssd
https://github.com/zqplgl/caffe
https://gitlab.com/birder/birder
https://gitlab.com/matzkin/deep-brain-extractor
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.