https://github.com/2023-MindSpore-1/ms-code-220/tree/main/EDCN
EDCNN: Edge enhancement-based Densely Connected Network with Compound Loss for Low-Dose CT Denoising
Papers with Code 아카이브
Denoising
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
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- 보존된 평가 기록
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Denoising is a task in image processing and computer vision that aims to remove or reduce noise from an image. Noise can be introduced into an image due to various reasons, such as camera sensor limitations, lighting conditions, and compression artifacts. The goal of denoising is to recover the original image, which is considered to be noise-free, from a noisy observation.
<span style="color:grey; opacity: 0.6">( Image credit: Beyond a Gaussian Denoiser )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/2023-MindSpore-1/ms-code-6/tree/main/brdnet
A Multi-Head Convolutional Neural Network With Multi-path Attention improves Image Denoising
https://github.com/2023-MindSpore-4/Code-5/tree/main/HiFaceGAN
HiFaceGAN: Face Renovation via Collaborative Suppression and Replenishment
https://github.com/2023-MindSpore-4/Code-5/tree/main/IndexNet
https://github.com/2023-MindSpore-4/Code-5/tree/main/LearningToSeeInTheDark
https://github.com/2023-MindSpore-4/Code-5/tree/main/MIMO-UNet
https://github.com/2023-MindSpore-4/Code-5/tree/main/llnet
LLNet: A Deep Autoencoder Approach to Natural Low-light Image Enhancement
https://github.com/2023-MindSpore-4/Code12/tree/main/d2l/chapter_03_linear-networks
https://github.com/2023-MindSpore-4/Code2/tree/main/DDM
DDM$^2$: Self-Supervised Diffusion MRI Denoising with Generative Diffusion Models
https://github.com/2023-MindSpore-4/Code3/tree/main/DnCNN
https://github.com/2023-MindSpore-4/Code5/tree/main/IFRQE
IFR-Net: Iterative Feature Refinement Network for Compressed Sensing MRI
https://github.com/2023-MindSpore-4/Code6/tree/main/RDN
https://github.com/2024-MindSpore-1/Code2/tree/main/model-1/bart
https://github.com/2024-MindSpore-1/Code2/tree/main/model-1/bartpho
BARTpho: Pre-trained Sequence-to-Sequence Models for Vietnamese
https://github.com/2024-MindSpore-1/Code6/tree/main/brdnet
A Multi-Head Convolutional Neural Network With Multi-path Attention improves Image Denoising
https://github.com/7568/ffdnet-pytorch
FFDNet: Toward a Fast and Flexible Solution for CNN based Image Denoising
https://github.com/AI-for-Ocean-Science/ulmo
https://github.com/AbIsuNav/DD2412_project
Variational Denoising Network: Toward Blind Noise Modeling and Removal
https://github.com/AbhinavS99/Ladder-Networks-for-Sign-Languages
https://github.com/AdneneBoumessouer/Anomaly-Detection
Image Restoration Using Convolutional Auto-encoders with Symmetric Skip Connections
https://github.com/AdneneBoumessouer/LEGO-Anomaly-Detection
Image Restoration Using Convolutional Auto-encoders with Symmetric Skip Connections
https://github.com/AdneneBoumessouer/MVTec-Anomaly-Detection
Image Restoration Using Convolutional Auto-encoders with Symmetric Skip Connections
https://github.com/Aftaab99/DenoisingAutoencoder
https://github.com/Agchai52/Linear-Time-Algorithm-in-Bayesian-Image-Denoising-Based-on-Gaussian-Markov-Random-Field
Linear-Time Algorithm in Bayesian Image Denoising based on Gaussian Markov Random Field
https://github.com/AlbertZhangHIT/CNN-POCS
Can learning from natural image denoising be used for seismic data interpolation?
https://github.com/AniSundar18/AlignedForensics
On the Effectiveness of Dataset Alignment for Fake Image Detection
https://github.com/AniketP04/Credit-Card-Fraud-Detection
Credit Card Fraud Detection Using Autoencoder Neural Network
https://github.com/Aoi-hosizora/FFDNet_pytorch
FFDNet: Toward a Fast and Flexible Solution for CNN based Image Denoising
https://github.com/AryaKoureshi/Magnocellular-Parvocellular-Coactivation-Task-in-MATLAB
EEG Connectivity Analysis Using Denoising Autoencoders for the Detection of Dyslexia
https://github.com/Ashwin-Pokharel/base_diffusion
https://github.com/Audio-WestlakeU/FullSubNet/blob/main/audio_zen/acoustics/rvb.py
Speech Dereverberation with a Reverberation Time Shortening Target
https://github.com/AureliePeng/Keras-WaveletTransform
https://github.com/BH94/cGANs-tensorflow-Python
Sharpness-aware Low dose CT denoising using conditional generative adversarial network
https://github.com/Baymax-chen/EMVD
Efficient Multi-Stage Video Denoising with Recurrent Spatio-Temporal Fusion
https://github.com/BjoernNieth/LS-Dataset-pruning-in-AT
Better Diffusion Models Further Improve Adversarial Training
https://github.com/BlackPepperAPI/Cadene.pytorch
FastDVDnet: Towards Real-Time Deep Video Denoising Without Flow Estimation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.