计算机辅助设计与图形学学报最新文献_第6页

Non-Uniform B-Spline Curve Interpolation Method for Feature Points Selection under Curvature Adaptive Condition 曲率自适应条件下特征点选择的非均匀B样条曲线插值方法

计算机辅助设计与图形学学报 Pub Date : 2021-09-01 DOI: 10.3724/sp.j.1089.2021.18366

Liangji Chen, Fei Gao, Bo Zhao, Longfei Ma

引用次数: 0

The Design and Optimization of Ship Cabin Space Layout Based on Crowd Simulation 基于人群仿真的船舶舱室空间布局设计与优化

计算机辅助设计与图形学学报 Pub Date : 2021-09-01 DOI: 10.3724/sp.j.1089.2021.18822

Pei Lyu, Weichao Chen, Quan Zhang, Mingliang Xu, Long Huang, Chenbing Guo, Bing Zhou

引用次数: 1

Time Series Denoising Using Nonlinear Schrödinger Equation 非线性Schrödinger方程的时间序列去噪

计算机辅助设计与图形学学报 Pub Date : 2021-08-01 DOI: 10.3724/sp.j.1089.2021.18671

Yifan Lei, Gang Song, Chengyong Gao, Fangxun Bao, Yunfeng Zhang

引用次数: 0

Local Banking to 45°: Axis Grid Generation for Line Charts 本地银行到45°:轴网格生成折线图

计算机辅助设计与图形学学报 Pub Date : 2021-08-01 DOI: 10.3724/sp.j.1089.2021.18660

Chen Bao, Yunhai Wang

引用次数: 0

Machine Learning Methods in Medical Image Compression 医学图像压缩中的机器学习方法

计算机辅助设计与图形学学报 Pub Date : 2021-08-01 DOI: 10.3724/sp.j.1089.2021.18687

Yuxuan Hou, Yining Di, Zhong Ren, Y. Tao, Wei Chen

{"title":"Machine Learning Methods in Medical Image Compression","authors":"Yuxuan Hou, Yining Di, Zhong Ren, Y. Tao, Wei Chen","doi":"10.3724/sp.j.1089.2021.18687","DOIUrl":"https://doi.org/10.3724/sp.j.1089.2021.18687","url":null,"abstract":"A large amount of image data such as CT that needs storage and transmission is generated in medical research. It is hard for the hospital to handle all data of the numerous patients. Therefore, it is of vital importance to compress these image data. Recently, learning-based medical image compression has become a new research trend with the development of artificial intelligence. Traditional methods in medical data compression are firstly reviewed. Further study in learning-based approaches is made, and the compression performance of these approaches in different medical image data such as brain CT and liver CT are shown. In the meantime, the advantages and disadvantages of these approaches in various aspects such as compression ratio, algorithm complexity and reconstruction quality are systematically summarized. It is pointed out that the combination of learning-based method and ROI-based method achieves high compression ratio brought by lossy compression, while keeping the feature information of the critical regions. Consequently, this approach is much more suitable for medical image compression than others. Finally, the paper concluded with a discussion of future development in this field.","PeriodicalId":52442,"journal":{"name":"计算机辅助设计与图形学学报","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47629041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Survey on OD Data Visualization OD数据可视化研究综述

计算机辅助设计与图形学学报 Pub Date : 2021-08-01 DOI: 10.3724/sp.j.1089.2021.18679

Le Tu, Binjie Chen, Zhiguang Zhou

引用次数: 0

Streamgraph Generation with Enhanced Readability 具有增强可读性的流图生成

计算机辅助设计与图形学学报 Pub Date : 2021-08-01 DOI: 10.3724/sp.j.1089.2021.18688

Chuan Bu, Quanjie Zhang, Yunhai Wang, Peng Jiang

引用次数: 0

DEM-cGAN Framework Constrained by Feature Lines and Elevation Range 特征线和高程约束的DEM-cGAN框架

计算机辅助设计与图形学学报 Pub Date : 2021-08-01 DOI: 10.3724/sp.j.1089.2021.18656

Xiling Jiang, ShaoRong Wang, Wenyu Li, Guoping Wang

引用次数: 1

Glandular Cell Segmentation Method Combined with Dense Connective Blocks and Self-Attention Mechanism 结合密集连接块和自注意机制的腺细胞分割方法

计算机辅助设计与图形学学报 Pub Date : 2021-07-01 DOI: 10.3724/sp.j.1089.2021.18625

Baoqi Zhao, Fei Yu, Junmei Sun, Xiumei Li, L. Yuan, Lei Xiao

引用次数: 0

Improved Efficient Convolutional Neural Networks for Complex Scene Mask-Wearing Detection 用于复杂场景戴口罩检测的改进高效卷积神经网络

计算机辅助设计与图形学学报 Pub Date : 2021-07-01 DOI: 10.3724/sp.j.1089.2021.18635

Junxiao Xue, Junjin Cheng, Qibin Zhang, Yibo Guo, Aiguo Lu, Jian Li, Xi Wan, Jing Xu

{"title":"Improved Efficient Convolutional Neural Networks for Complex Scene Mask-Wearing Detection","authors":"Junxiao Xue, Junjin Cheng, Qibin Zhang, Yibo Guo, Aiguo Lu, Jian Li, Xi Wan, Jing Xu","doi":"10.3724/sp.j.1089.2021.18635","DOIUrl":"https://doi.org/10.3724/sp.j.1089.2021.18635","url":null,"abstract":": To solve the problem about low accuracy of mask wear detection under complex lighting and face lean conditions, a method of mask wear detection under intricate environment using efficient convolutional neural network is proposed, which uses pre-training such as hard negative mining to learn more samples of face feature, utilize multi-task convolutional neural networks (MTCNN) to estimate the possibility of face information, and get accurate face location. With attention mechanism in feature pyramid network, enhanc-ing the weight of key points on human face, employing efficient neural network detection will be wore on mask-wearing detection as a simple binary classification problem. Under the environment of TensorFlow platform, not only data training, data preprocessing, but also the contrast experiment with AIZOO method are completed. A data set containing with 816 images is collected, marked and trained. During the data pre-processing, images are set as fixed size to reduce the amount of computation and promote the detection speed. Then, image enhancement algorithm is used to conduct distortion processing to improve the robust-ness of this model. On this basis, MTCNN is used to detect the face information in pictures, modify and normalize all data, then put them into neural network and the trained model to detection. The experimental results show that under complex conditions such as complex lighting and face tilt, the accuracy can reach 83% and 91% respectively, which means can accurately detect whether wearing a mask.","PeriodicalId":52442,"journal":{"name":"计算机辅助设计与图形学学报","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46256511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1