Methods for image denoising using convolutional neural network: a review
AE Ilesanmi, TO Ilesanmi - Complex & Intelligent Systems, 2021 - Springer
Image denoising faces significant challenges, arising from the sources of noise. Specifically,
Gaussian, impulse, salt, pepper, and speckle noise are complicated sources of noise in …
Gaussian, impulse, salt, pepper, and speckle noise are complicated sources of noise in …
Recent advances of deep learning algorithms for aquacultural machine vision systems with emphasis on fish
D Li, L Du - Artificial Intelligence Review, 2022 - Springer
Monitoring the growth conditions and behavior of fish will enable scientific management,
reduce the threat of losses caused by disease and stress. Traditional monitoring methods …
reduce the threat of losses caused by disease and stress. Traditional monitoring methods …
Image-to-image regression with distribution-free uncertainty quantification and applications in imaging
Image-to-image regression is an important learning task, used frequently in biological
imaging. Current algorithms, however, do not generally offer statistical guarantees that …
imaging. Current algorithms, however, do not generally offer statistical guarantees that …
[HTML][HTML] Relation between prognostics predictor evaluation metrics and local interpretability SHAP values
Maintenance decisions in domains such as aeronautics are becoming increasingly
dependent on being able to predict the failure of components and systems. When data …
dependent on being able to predict the failure of components and systems. When data …
A fast blind zero-shot denoiser
Image noise is a common problem in light microscopy. This is particularly true in real-time
live-cell imaging applications in which long-term cell viability necessitates low-light …
live-cell imaging applications in which long-term cell viability necessitates low-light …
Deep learning in electron microscopy
JM Ede - Machine Learning: Science and Technology, 2021 - iopscience.iop.org
Deep learning is transforming most areas of science and technology, including electron
microscopy. This review paper offers a practical perspective aimed at developers with …
microscopy. This review paper offers a practical perspective aimed at developers with …
Nucleus segmentation: towards automated solutions
Single nucleus segmentation is a frequent challenge of microscopy image processing, since
it is the first step of many quantitative data analysis pipelines. The quality of tracking single …
it is the first step of many quantitative data analysis pipelines. The quality of tracking single …
Soil organic matter prediction model with satellite hyperspectral image based on optimized denoising method
X Meng, Y Bao, Q Ye, H Liu, X Zhang, H Tang… - Remote Sensing, 2021 - mdpi.com
In order to improve the signal-to-noise ratio of the hyperspectral sensors and exploit the
potential of satellite hyperspectral data for predicting soil properties, we took MingShui …
potential of satellite hyperspectral data for predicting soil properties, we took MingShui …
Ddunet: Dense dense u-net with applications in image denoising
The investigation of CNN for image denoising has arrived at a serious bottleneck and it is
extremely difficult to design an efficient network for image denoising with better performance …
extremely difficult to design an efficient network for image denoising with better performance …
Image and video processing on mobile devices: a survey
C Morikawa, M Kobayashi, M Satoh, Y Kuroda… - The Visual …, 2021 - Springer
Image processing and computer vision on mobile devices have a wide range of applications
such as digital image enhancement and augmented reality. While images acquired by …
such as digital image enhancement and augmented reality. While images acquired by …