中国图象图形学报最新文献

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Gray Level Co-occurrence Matrix with Binary Robust Invariant Scalable Keypoints for Detecting Copy Move Forgeries 基于二值鲁棒不变可伸缩关键点的灰度共生矩阵检测复制移动伪造
中国图象图形学报 Pub Date : 2023-03-01 DOI: 10.18178/joig.11.1.82-90
Amarpreet Singh, Sanjogdeep Singh
{"title":"Gray Level Co-occurrence Matrix with Binary Robust Invariant Scalable Keypoints for Detecting Copy Move Forgeries","authors":"Amarpreet Singh, Sanjogdeep Singh","doi":"10.18178/joig.11.1.82-90","DOIUrl":"https://doi.org/10.18178/joig.11.1.82-90","url":null,"abstract":"With advancement in technology, especially in imaging field, digital image forgery has increased a lot nowadays. In order to counter this problem, many forgery detection techniques have been developed from time to time. For rapid and accurate detection of forged image, a novel hybrid technique is used in this research work that implements Gray Level Co-occurrence Matrix (GLCM) along with Binary Robust Invariant Scalable Keypoints (BRISK). GLCM significantly extracts key attributes from an image efficiently which will help to increase the detection accuracy. BRISK is known to be one of the 3 fastest modes of detection which will increase the execution speed of GLCM. BRISK even processes scaled and rotated images. Then the Principal Component Analysis (PCA) algorithm is applied in the final phase of detection will remove any unrequited element from the scene and highlights the concerned forged area.","PeriodicalId":36336,"journal":{"name":"中国图象图形学报","volume":"68 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75036383","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
Intelligent visualization and visual analytics 智能可视化和可视化分析
中国图象图形学报 Pub Date : 2023-01-01 DOI: 10.11834/jig.230034
Tao Jun, Zhang Yu, Chen Qing, Liu Can, Siming Chen, Xiaoru Yuan
{"title":"Intelligent visualization and visual analytics","authors":"Tao Jun, Zhang Yu, Chen Qing, Liu Can, Siming Chen, Xiaoru Yuan","doi":"10.11834/jig.230034","DOIUrl":"https://doi.org/10.11834/jig.230034","url":null,"abstract":"","PeriodicalId":36336,"journal":{"name":"中国图象图形学报","volume":"156 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77482578","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
Review of optimization methods for supervised deep learning 有监督深度学习的优化方法综述
中国图象图形学报 Pub Date : 2023-01-01 DOI: 10.11834/jig.211139
Lin Jiang, Yifeng Zheng, Chen Che, Li Guohe, Wenjie Zhang
{"title":"Review of optimization methods for supervised deep learning","authors":"Lin Jiang, Yifeng Zheng, Chen Che, Li Guohe, Wenjie Zhang","doi":"10.11834/jig.211139","DOIUrl":"https://doi.org/10.11834/jig.211139","url":null,"abstract":": Deep learning technique has been developing intensively in big data era. However , its capability is still chal⁃ lenged for the design of network structure and parameter setting. Therefore , it is essential to improve the performance of the model and optimize the complexity of the model. Machine learning can be segmented into five categories in terms of learn⁃ ing methods : 1 ) supervised learning , 2 ) unsupervised learning , 3 ) semi - supervised learning , 4 ) deep learning , and 5 ) reinforcement learning. These machine learning techniques are required to be incorporated in. To improve its fitting and","PeriodicalId":36336,"journal":{"name":"中国图象图形学报","volume":"22 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80080636","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
Temporal series features extraction based on Bi-ConvLSTM of Alzheimer’s disease pridiction CTISS model 基于Bi-ConvLSTM的阿尔茨海默病预测CTISS模型时间序列特征提取
中国图象图形学报 Pub Date : 2023-01-01 DOI: 10.11834/jig.211186
Hong Xin, Kaifeng Huang, Chenhui Yang
{"title":"Temporal series features extraction based on Bi-ConvLSTM of Alzheimer’s disease pridiction CTISS model","authors":"Hong Xin, Kaifeng Huang, Chenhui Yang","doi":"10.11834/jig.211186","DOIUrl":"https://doi.org/10.11834/jig.211186","url":null,"abstract":"","PeriodicalId":36336,"journal":{"name":"中国图象图形学报","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81878764","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
Review on optical visual sensor technology 光学视觉传感器技术综述
中国图象图形学报 Pub Date : 2023-01-01 DOI: 10.11834/jig.230039
Xu Jiangtao, Wang Xinyang, Wang Tingdong, Chen Xin, Song Zongxi, Lei Hao, Liu Gang, Wen Desheng
{"title":"Review on optical visual sensor technology","authors":"Xu Jiangtao, Wang Xinyang, Wang Tingdong, Chen Xin, Song Zongxi, Lei Hao, Liu Gang, Wen Desheng","doi":"10.11834/jig.230039","DOIUrl":"https://doi.org/10.11834/jig.230039","url":null,"abstract":"","PeriodicalId":36336,"journal":{"name":"中国图象图形学报","volume":"162 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73306483","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 review of forest visualization and forest fire simulation technology research 森林可视化与森林火灾模拟技术研究综述
中国图象图形学报 Pub Date : 2023-01-01 DOI: 10.11834/jig.230016
Huai Yongjian, Qingkuo Meng, Tianrong Ma, Haifeng Xu, Zhao Xi, Mingzhi Cheng, Xinyuan Huang
{"title":"A review of forest visualization and forest fire simulation technology research","authors":"Huai Yongjian, Qingkuo Meng, Tianrong Ma, Haifeng Xu, Zhao Xi, Mingzhi Cheng, Xinyuan Huang","doi":"10.11834/jig.230016","DOIUrl":"https://doi.org/10.11834/jig.230016","url":null,"abstract":"","PeriodicalId":36336,"journal":{"name":"中国图象图形学报","volume":"32 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78676638","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
AsymcNet:a document images-relevant asymmetric geometry correction network 一个文档图像相关的非对称几何校正网络
中国图象图形学报 Pub Date : 2023-01-01 DOI: 10.11834/jig.220426
Qin Hai, Li Yijie, Q. Liang, Yaonan Wang
{"title":"AsymcNet:a document images-relevant asymmetric geometry correction network","authors":"Qin Hai, Li Yijie, Q. Liang, Yaonan Wang","doi":"10.11834/jig.220426","DOIUrl":"https://doi.org/10.11834/jig.220426","url":null,"abstract":"","PeriodicalId":36336,"journal":{"name":"中国图象图形学报","volume":"48 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88266511","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
Pre analysis of difficulty in renal tumor enucleation surgery based on deep learning and image automation evaluation 基于深度学习和图像自动化评价的肾肿瘤去核手术难度预分析
中国图象图形学报 Pub Date : 2023-01-01 DOI: 10.11834/jig.220375
Yunpeng Liu, Tielin Wu, Cai Wenli, Renfang Wang, Dechao Sun, Kaifeng Gan, Li Jin, Jin Ran, Qiu Hong, Huixia Xu
{"title":"Pre analysis of difficulty in renal tumor enucleation surgery based on deep learning and image automation evaluation","authors":"Yunpeng Liu, Tielin Wu, Cai Wenli, Renfang Wang, Dechao Sun, Kaifeng Gan, Li Jin, Jin Ran, Qiu Hong, Huixia Xu","doi":"10.11834/jig.220375","DOIUrl":"https://doi.org/10.11834/jig.220375","url":null,"abstract":"","PeriodicalId":36336,"journal":{"name":"中国图象图形学报","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89224199","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
Video anomaly detection by fusing self-attention and autoencoder 融合自关注和自编码器的视频异常检测
中国图象图形学报 Pub Date : 2023-01-01 DOI: 10.11834/jig.211147
Jiafei Liang, Li Ting, Yang Jiaqi, Li Yanan, Zhiwen Fang, Yang Feng
{"title":"Video anomaly detection by fusing self-attention and autoencoder","authors":"Jiafei Liang, Li Ting, Yang Jiaqi, Li Yanan, Zhiwen Fang, Yang Feng","doi":"10.11834/jig.211147","DOIUrl":"https://doi.org/10.11834/jig.211147","url":null,"abstract":": Objective Anomaly detection has been developing in video surveillance domain. Video anomaly detection is","PeriodicalId":36336,"journal":{"name":"中国图象图形学报","volume":"136 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79602862","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
Research on visual analysis methods of bird satellite tracking data: a case study analysis for Nipponia nippon 鸟类卫星跟踪数据的可视化分析方法研究——以日本鸟为例
中国图象图形学报 Pub Date : 2023-01-01 DOI: 10.11834/jig.220403
Xinyue Li, Jiang Xian, Weiqun Cao, Dongping Liu
{"title":"Research on visual analysis methods of bird satellite tracking data: a case study analysis for Nipponia nippon","authors":"Xinyue Li, Jiang Xian, Weiqun Cao, Dongping Liu","doi":"10.11834/jig.220403","DOIUrl":"https://doi.org/10.11834/jig.220403","url":null,"abstract":"","PeriodicalId":36336,"journal":{"name":"中国图象图形学报","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85350443","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
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