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计算机辅助设计与图形学学报最新文献

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Weakly Supervised Surface Defect Detection Based on Attention Mechanism 基于注意力机制的弱监督表面缺陷检测
计算机辅助设计与图形学学报 Pub Date : 2021-06-01 DOI: 10.3724/sp.j.1089.2021.18594
Meijun Sun, Chaozhang Lyu, Yahong Han, Sen Li, Z. Wang
{"title":"Weakly Supervised Surface Defect Detection Based on Attention Mechanism","authors":"Meijun Sun, Chaozhang Lyu, Yahong Han, Sen Li, Z. Wang","doi":"10.3724/sp.j.1089.2021.18594","DOIUrl":"https://doi.org/10.3724/sp.j.1089.2021.18594","url":null,"abstract":"","PeriodicalId":52442,"journal":{"name":"计算机辅助设计与图形学学报","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43281878","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: 2
Identity-Aware Facial Expression Recognition Method Based on Synthesized Images and Deep Metric Learning 基于合成图像和深度度量学习的身份感知面部表情识别方法
计算机辅助设计与图形学学报 Pub Date : 2021-05-01 DOI: 10.3724/sp.j.1089.2021.18462
Siyuan Zhang, Shiming Xiao, Peng Zhang, Wei Huang
{"title":"Identity-Aware Facial Expression Recognition Method Based on Synthesized Images and Deep Metric Learning","authors":"Siyuan Zhang, Shiming Xiao, Peng Zhang, Wei Huang","doi":"10.3724/sp.j.1089.2021.18462","DOIUrl":"https://doi.org/10.3724/sp.j.1089.2021.18462","url":null,"abstract":": Facial expression recognition (FER) is a challenging task because the external environment and identity characteristics could affect the classification results directly. To settle down the above-mentioned challenges, this paper proposed an identity-aware facial expression recognition method which combined images synthesis techniques and deep metric learning, and made facial images features compared then clas-sified by creating expression groups under the same identity in FER task. There are three parts in our method. The first part is a generative adversarial network, which aims to learn expression information and synthesis the expression groups. the state-of-the-art methods, the experimental results confirmed that the proposed-method was effective and progressive in FER task.","PeriodicalId":52442,"journal":{"name":"计算机辅助设计与图形学学报","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45449248","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
Hair Attribute Transfer via Deep Feature Fusion 通过深度特征融合的头发属性转移
计算机辅助设计与图形学学报 Pub Date : 2021-05-01 DOI: 10.3724/sp.j.1089.2021.18544
Zhifeng Xie, Xu Su, Siwei Liu, Guisong Zhang, Lizhuang Ma
{"title":"Hair Attribute Transfer via Deep Feature Fusion","authors":"Zhifeng Xie, Xu Su, Siwei Liu, Guisong Zhang, Lizhuang Ma","doi":"10.3724/sp.j.1089.2021.18544","DOIUrl":"https://doi.org/10.3724/sp.j.1089.2021.18544","url":null,"abstract":": To tackle the problem that existing attribute transfer methods can’t transfer hair attributes effectively, a method of hair attribute transfer based on deep feature fusion is presented. This method includes three subnetworks which are responsible for feature extraction, attribute vector extraction and image synthesis. Firstly, feature extraction network extracts features from original images, and keeps the identity of original images unchanged by adding a reconstruction loss. At the same time, attribute vector extraction network constructs the mapping model of hair features and hair attributes","PeriodicalId":52442,"journal":{"name":"计算机辅助设计与图形学学报","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42178363","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
Isolated Routing Algorithm without Virtual Channels for Network-on-Chip 片上网络无虚拟通道隔离路由算法
计算机辅助设计与图形学学报 Pub Date : 2021-05-01 DOI: 10.3724/sp.j.1089.2021.18535
Ruilian Xie, Jiye Jiao, Youyao Liu
{"title":"Isolated Routing Algorithm without Virtual Channels for Network-on-Chip","authors":"Ruilian Xie, Jiye Jiao, Youyao Liu","doi":"10.3724/sp.j.1089.2021.18535","DOIUrl":"https://doi.org/10.3724/sp.j.1089.2021.18535","url":null,"abstract":"","PeriodicalId":52442,"journal":{"name":"计算机辅助设计与图形学学报","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48076023","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
Hash Self-Attention End-to-End Network for Sketch-Based 3D Shape Retrieval 基于草图的三维形状检索的Hash自关注端到端网络
计算机辅助设计与图形学学报 Pub Date : 2021-05-01 DOI: 10.3724/sp.j.1089.2021.18548
Xufei Zhao, Xiang Pan, Fuchang Liu, S. Zhang
{"title":"Hash Self-Attention End-to-End Network for Sketch-Based 3D Shape Retrieval","authors":"Xufei Zhao, Xiang Pan, Fuchang Liu, S. Zhang","doi":"10.3724/sp.j.1089.2021.18548","DOIUrl":"https://doi.org/10.3724/sp.j.1089.2021.18548","url":null,"abstract":"","PeriodicalId":52442,"journal":{"name":"计算机辅助设计与图形学学报","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44366278","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
Layout Design of Medical Terminal Interface Combining User-Oriented andGenetic Algorithm 结合用户导向和遗传算法的医疗终端界面布局设计
计算机辅助设计与图形学学报 Pub Date : 2021-05-01 DOI: 10.3724/sp.j.1089.2021.18338
Yuanfeng Li, Qun Wu, Jian Zhang, Rong Niu, Yifan Zhu, Jiecong Zong
{"title":"Layout Design of Medical Terminal Interface Combining User-Oriented andGenetic Algorithm","authors":"Yuanfeng Li, Qun Wu, Jian Zhang, Rong Niu, Yifan Zhu, Jiecong Zong","doi":"10.3724/sp.j.1089.2021.18338","DOIUrl":"https://doi.org/10.3724/sp.j.1089.2021.18338","url":null,"abstract":": In order to achieve the optimal interface design of the public terminal while improving user experience, this paper proposes an interface layout method that combines user orientation and a genetic algorithm. According to this method, the subjective cognition of users and their objective vision principle are integrated before conversion into a layout index. With the index of the interface layout scheme taken as the independent variable and the user experience value as the dependent variable, the cognitive relationship be-tween the interface layout index and subjective user experience was modeled as a computable function. The expansion solution space was searched after the interface layout features were encoded using the slicing tree method. The specific steps include generating tree structure, determining the cutting method to obtain the best section tree, and adjusting the element nodes to identify the most satisfactory layout. With the registra-tion interface and payment interface of the medical public terminal as an example, this method was applied to optimize its layout and then verified through a usability test. According to the experimental results, the usability indicators of the optimized interface layout was improved more significantly compared with the initial interface, suggesting the effectiveness of this method in the application of medical terminal interface design scenarios. Moreover, the generative auxiliary design of this kind is conducive to reducing the work-load placed on designers and to enhancing efficiency.","PeriodicalId":52442,"journal":{"name":"计算机辅助设计与图形学学报","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43647370","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
Bionic SLAM Algorithm Based on Multi-Scale Grid Cell to Place Cell 基于多尺度网格细胞到位置细胞的仿生SLAM算法
计算机辅助设计与图形学学报 Pub Date : 2021-05-01 DOI: 10.3724/sp.j.1089.2021.18407
Mengyuan Chen, De-run Tian
{"title":"Bionic SLAM Algorithm Based on Multi-Scale Grid Cell to Place Cell","authors":"Mengyuan Chen, De-run Tian","doi":"10.3724/sp.j.1089.2021.18407","DOIUrl":"https://doi.org/10.3724/sp.j.1089.2021.18407","url":null,"abstract":": Aiming at the problems of low positioning accuracy and angle drift in the process of simultaneous localization and mapping (SLAM), inspired by the spatial cognitive mechanism of mammalian hippocampus, a bionic SLAM algorithm for constructing information conversion from multi-scale grid cell to place cell is proposed. Firstly, the proposed algorithm introduces head direction cell and stripe cell to perceive their own motion information while generating a multi-scale grid cell to cover the entire spatial environment, which can reduce the cu-mulative error due to angular offset. Secondly, as for the problem of low localization accuracy, the proposed algorithm uses a competitive neural network under Hebb learning rule to establish the information conversion relationship from multi-scale grid cell to place cell. Meanwhile, the mapping relationship between place cell and dif-ferent landmarks in the spatial environment is constructed. Finally, the place cells with the maximum discharge rate are selected in order to form spatial cognitive topological map while realizing the autonomous localization of mobile robots. Compared with RatSLAM and ORB-SLAM2 on the KITTI public dataset, the results show that the proposed algorithm can realize autonomous localization and mapping in unknown environments by encoding the location information, while controlling the translation error at no more than 1.50 m and the rotation error at no higher than 1.0°.","PeriodicalId":52442,"journal":{"name":"计算机辅助设计与图形学学报","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43998653","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: 2
Self-Weighted Multi-View Metric Learning and Its Application for Remote Sensing Image Scene Classification 自加权多视图度量学习及其在遥感图像场景分类中的应用
计算机辅助设计与图形学学报 Pub Date : 2021-05-01 DOI: 10.3724/sp.j.1089.2021.18571
G. Zhou, Hui Jiang, Xiaoqing Gu, Xinchun Yin
{"title":"Self-Weighted Multi-View Metric Learning and Its Application for Remote Sensing Image Scene Classification","authors":"G. Zhou, Hui Jiang, Xiaoqing Gu, Xinchun Yin","doi":"10.3724/sp.j.1089.2021.18571","DOIUrl":"https://doi.org/10.3724/sp.j.1089.2021.18571","url":null,"abstract":"","PeriodicalId":52442,"journal":{"name":"计算机辅助设计与图形学学报","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45936312","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
A Novelty Detection Algorithm in the Presence of Noise 一种存在噪声的新颖性检测算法
计算机辅助设计与图形学学报 Pub Date : 2021-05-01 DOI: 10.3724/sp.j.1089.2021.18540
Fanxia Zeng, Zewen He, Wensheng Zhang
{"title":"A Novelty Detection Algorithm in the Presence of Noise","authors":"Fanxia Zeng, Zewen He, Wensheng Zhang","doi":"10.3724/sp.j.1089.2021.18540","DOIUrl":"https://doi.org/10.3724/sp.j.1089.2021.18540","url":null,"abstract":": To address the poor performance of novelty detection in the presence of noisy samples, a method named kernel null space discriminant locality preserving projections (KNDLPP) is proposed. Firstly, the training samples are transformed into a high dimensional space through a kernel function implicitly, and different weights are assigned to these samples according to the distance weighted scheme in the UCI datasets, the whole mean AUC of KNDLPP is 90.656%. During the experiments about complex structure on Banana, Moon and 3 UCI datasets, the whole mean AUC of KNDLPP is 91.949%. During the experiments on 2 clean high dimensional datasets for novelty detection, the whole mean AUC of KNDLPP is 86.214%, which is 4 percent higher than the second best algorithm. On 4 UCI datasets with 4 different kinds of noise, the performance of KNDLPP ranks first.","PeriodicalId":52442,"journal":{"name":"计算机辅助设计与图形学学报","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41945171","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
Object Detection in Real-World Hazy Scene 真实世界模糊场景中的目标检测
计算机辅助设计与图形学学报 Pub Date : 2021-05-01 DOI: 10.3724/sp.j.1089.2021.18554
Yuhong Xie, Yuan Xie, Liang Chen, Cuihua Li, Yanyun Qu
{"title":"Object Detection in Real-World Hazy Scene","authors":"Yuhong Xie, Yuan Xie, Liang Chen, Cuihua Li, Yanyun Qu","doi":"10.3724/sp.j.1089.2021.18554","DOIUrl":"https://doi.org/10.3724/sp.j.1089.2021.18554","url":null,"abstract":"","PeriodicalId":52442,"journal":{"name":"计算机辅助设计与图形学学报","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48633262","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: 2
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