关注
Nan Mu
Nan Mu
Sichuan Normal University
在 sicnu.edu.cn 的电子邮件经过验证
标题
引用次数
引用次数
年份
Progressive global perception and local polishing network for lung infection segmentation of COVID-19 CT images
N Mu, H Wang, Y Zhang, J Jiang, J Tang
Pattern Recognition 120, 108168, 2021
632021
An attention residual u-net with differential preprocessing and geometric postprocessing: Learning how to segment vasculature including intracranial aneurysms
N Mu, Z Lyu, M Rezaeitaleshmahalleh, J Tang, J Jiang
Medical image analysis 84, 102697, 2023
402023
Eye-gaze tracking system by haar cascade classifier
Y Li, X Xu, N Mu, L Chen
2016 IEEE 11th Conference on Industrial Electronics and Applications (ICIEA …, 2016
292016
Salient object detection using a covariance-based CNN model in low-contrast images
N Mu, X Xu, X Zhang, H Zhang
Neural Computing and Applications 29, 181-192, 2018
272018
Salient object detection from distinctive features in low contrast images
X Xu, N Mu, H Zhang, X Fu
2015 IEEE international conference on image processing (ICIP), 3126-3130, 2015
252015
Hierarchical salient object detection model using contrast-based saliency and color spatial distribution
X Xu, N Mu, L Chen, X Zhang
Multimedia Tools and Applications 75, 2667-2679, 2016
212016
Saliency detection based on the combination of high-level knowledge and low-level cues in foggy images
X Zhu, X Xu, N Mu
Entropy 21 (4), 374, 2019
152019
Discrete stationary wavelet transform based saliency information fusion from frequency and spatial domain in low contrast images
N Mu, X Xu, X Zhang, X Lin
Pattern Recognition Letters 115, 84-91, 2018
152018
Salient object detection in low contrast images via global convolution and boundary refinement
N Mu, X Xu, X Zhang
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
132019
Covariance descriptor based convolution neural network for saliency computation in low contrast images
X Xu, N Mu, X Zhang, B Li
2016 International Joint Conference on Neural Networks (IJCNN), 616-623, 2016
122016
Automatic segmentation of abdominal aortic aneurysms from CT angiography using a context-aware cascaded U-Net
N Mu, Z Lyu, M Rezaeitaleshmahalleh, X Zhang, T Rasmussen, ...
Computers in biology and medicine 158, 106569, 2023
112023
Finding autofocus region in low contrast surveillance images using CNN-based saliency algorithm
N Mu, X Xu, X Zhang
Pattern Recognition Letters 125, 124-132, 2019
92019
Radiomic-based textural analysis of intraluminal thrombus in aortic abdominal aneurysms: a demonstration of automated workflow
M Rezaeitaleshmahalleh, N Mu, Z Lyu, W Zhou, X Zhang, TE Rasmussen, ...
Journal of cardiovascular translational research 16 (5), 1123-1134, 2023
82023
Characterization of small abdominal aortic aneurysms' growth status using spatial pattern analysis of aneurismal hemodynamics
M Rezaeitaleshmahalleh, Z Lyu, N Mu, X Zhang, TE Rasmussen, ...
Scientific reports 13 (1), 13832, 2023
62023
Deep-learning-based image segmentation for image-based computational hemodynamic analysis of abdominal aortic aneurysms: a comparison study
Z Lyu, K King, M Rezaeitaleshmahalleh, D Pienta, N Mu, C Zhao, W Zhou, ...
Biomedical physics & engineering express 9 (6), 067001, 2023
52023
Using convolutional neural network-based segmentation for image-based computational fluid dynamics simulations of brain aneurysms: initial experience in automated model creation
M Rezaeitaleshmahalleh, Z Lyu, NAN Mu, J Jiang
Journal of mechanics in medicine and biology 23 (4), 2023
52023
Video salient object detection network with bidirectional memory and spatiotemporal constraints
H Wang, N Mu, Y Zhang
2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2021
52021
Remote sensing image scene classification based on scale-attention network
X BIAN, X FEI, N MU
Journal of Computer Applications 40 (3), 872, 2020
42020
Optimal feature selection for saliency seed propagation in low contrast images
N Mu, X Xu, X Zhang
Advances in Multimedia Information Processing–PCM 2018: 19th Pacific-Rim …, 2018
42018
Block-based salient region detection using a new spatial-spectral-domain contrast measure
N Mu, X Xu, L Chen, J Tian
2014 IEEE International Symposium on Multimedia, 86-89, 2014
42014
系统目前无法执行此操作,请稍后再试。
文章 1–20