Visual Computing for Industry, Biomedicine, and Art最新文献_第10页

Correction to: Hybrid image of three contents. 更正为三个内容的混合图像。

4区计算机科学

Visual Computing for Industry, Biomedicine, and Art Pub Date : 2020-03-24 DOI: 10.1186/s42492-020-00046-w

Peeraya Sripian, Yasushi Yamaguchi

引用次数: 0

Fused behavior recognition model based on attention mechanism. 基于注意力机制的融合行为识别模型。

4区计算机科学

Visual Computing for Industry, Biomedicine, and Art Pub Date : 2020-03-12 DOI: 10.1186/s42492-020-00045-x

Lei Chen, Rui Liu, Dongsheng Zhou, Xin Yang, Qiang Zhang

{"title":"Fused behavior recognition model based on attention mechanism.","authors":"Lei Chen, Rui Liu, Dongsheng Zhou, Xin Yang, Qiang Zhang","doi":"10.1186/s42492-020-00045-x","DOIUrl":"10.1186/s42492-020-00045-x","url":null,"abstract":"With the rapid development of deep learning technology, behavior recognition based on video streams has made great progress in recent years. However, there are also some problems that must be solved: (1) In order to improve behavior recognition performance, the models have tended to become deeper, wider, and more complex. However, some new problems have been introduced also, such as that their real-time performance decreases; (2) Some actions in existing datasets are so similar that they are difficult to distinguish. To solve these problems, the ResNet34-3DRes18 model, which is a lightweight and efficient two-dimensional (2D) and three-dimensional (3D) fused model, is constructed in this study. The model used 2D convolutional neural network (2DCNN) to obtain the feature maps of input images and 3D convolutional neural network (3DCNN) to process the temporal relationships between frames, which made the model not only make use of 3DCNN's advantages on video temporal modeling but reduced model complexity. Compared with state-of-the-art models, this method has shown excellent performance at a faster speed. Furthermore, to distinguish between similar motions in the datasets, an attention gate mechanism is added, and a Res34-SE-IM-Net attention recognition model is constructed. The Res34-SE-IM-Net achieved 71.85%, 92.196%, and 36.5% top-1 accuracy (The predicting label obtained from model is the largest one in the output probability vector. If the label is the same as the target label of the motion, the classification is correct.) respectively on the test sets of the HMDB51, UCF101, and Something-Something v1 datasets.","PeriodicalId":52384,"journal":{"name":"Visual Computing for Industry, Biomedicine, and Art","volume":"3 1","pages":"7"},"PeriodicalIF":0.0,"publicationDate":"2020-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7099545/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37796674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Review of heterogeneous material objects modeling in additive manufacturing. 增材制造中的异质材料物体建模综述。

4区计算机科学

Visual Computing for Industry, Biomedicine, and Art Pub Date : 2020-03-05 DOI: 10.1186/s42492-020-0041-6

Bin Li, Jianzhong Fu, Jiawei Feng, Ce Shang, Zhiwei Lin

引用次数: 0

Analytic time-of-flight positron emission tomography reconstruction: three-dimensional case. 解析飞行时间正电子发射层析成像重建:三维案例。

4区计算机科学

Visual Computing for Industry, Biomedicine, and Art Pub Date : 2020-02-17 DOI: 10.1186/s42492-020-0042-5

Gengsheng L Zeng, Ya Li, Qiu Huang

引用次数: 1

Hybrid image of three contents. 三种内容的混合图像。

4区计算机科学

Visual Computing for Industry, Biomedicine, and Art Pub Date : 2020-02-10 DOI: 10.1186/s42492-019-0036-3

Peeraya Sripian, Yasushi Yamaguchi

{"title":"Hybrid image of three contents.","authors":"Peeraya Sripian, Yasushi Yamaguchi","doi":"10.1186/s42492-019-0036-3","DOIUrl":"https://doi.org/10.1186/s42492-019-0036-3","url":null,"abstract":"A hybrid image allows multiple image interpretations to be modulated by the viewing distance. Originally, it can be constructed by combining the low and high spatial frequencies of two different images. The original hybrid image synthesis was limited to similar shapes of source images that were aligned in the edges, e.g., faces with a different expression, to produce an effective double image interpretation. In our previous work, we proposed a noise-inserted method for synthesizing a hybrid image from dissimilar shape images or unaligned images. In this work, we propose a novel method for adding an image to be seen from a middle viewing distance. The middle-frequency (MF) image is extracted by a special bandpass filter, which generates ringing while extracting only specified frequency bands. With this method, the middle frequency should be perceived as a meaningless pattern when viewed from a far distance and close up. A parameter tuning experiment was performed to determine the suitable cutoff frequencies for designing the filter for the MF image. We found that ringings of a suitable size could be used to make the middle frequency less noticeable when seen from far away.","PeriodicalId":52384,"journal":{"name":"Visual Computing for Industry, Biomedicine, and Art","volume":"3 1","pages":"4"},"PeriodicalIF":0.0,"publicationDate":"2020-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s42492-019-0036-3","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37795172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Painting image browser applying an associate-rule-aware multidimensional data visualization technique. 应用关联规则感知多维数据可视化技术的绘图图像浏览器。

4区计算机科学

Visual Computing for Industry, Biomedicine, and Art Pub Date : 2020-02-05 DOI: 10.1186/s42492-019-0040-7

Ayaka Kaneko, Akiko Komatsu, Takayuki Itoh, Florence Ying Wang

{"title":"Painting image browser applying an associate-rule-aware multidimensional data visualization technique.","authors":"Ayaka Kaneko, Akiko Komatsu, Takayuki Itoh, Florence Ying Wang","doi":"10.1186/s42492-019-0040-7","DOIUrl":"https://doi.org/10.1186/s42492-019-0040-7","url":null,"abstract":"Exploration of artworks is enjoyable but often time consuming. For example, it is not always easy to discover the favorite types of unknown painting works. It is not also always easy to explore unpopular painting works which looks similar to painting works created by famous artists. This paper presents a painting image browser which assists the explorative discovery of user-interested painting works. The presented browser applies a new multidimensional data visualization technique that highlights particular ranges of particular numeric values based on association rules to suggest cues to find favorite painting images. This study assumes a large number of painting images are provided where categorical information (e.g., names of artists, created year) is assigned to the images. The presented system firstly calculates the feature values of the images as a preprocessing step. Then the browser visualizes the multidimensional feature values as a heatmap and highlights association rules discovered from the relationships between the feature values and categorical information. This mechanism enables users to explore favorite painting images or painting images that look similar to famous painting works. Our case study and user evaluation demonstrates the effectiveness of the presented image browser.","PeriodicalId":52384,"journal":{"name":"Visual Computing for Industry, Biomedicine, and Art","volume":"3 1","pages":"3"},"PeriodicalIF":0.0,"publicationDate":"2020-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7099557/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37795050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Research on a bifurcation location algorithm of a drainage tube based on 3D medical images. 基于三维医学图像的引流管分岔定位算法研究。

4区计算机科学

Visual Computing for Industry, Biomedicine, and Art Pub Date : 2020-01-14 DOI: 10.1186/s42492-019-0039-0

Qiuling Pan, Wei Zhu, Xiaolin Zhang, Jincai Chang, Jianzhong Cui

引用次数: 4

Novel indoor positioning system based on ultra-wide bandwidth. 基于超宽带的新型室内定位系统。

4区计算机科学

Visual Computing for Industry, Biomedicine, and Art Pub Date : 2020-01-07 DOI: 10.1186/s42492-019-0038-1

Zhen Wei, Rui Jiang, Xing Wei, Yun-An Cheng, Lei Cheng, Cai Wang

引用次数: 7

Editorial: medical imaging modeling. 社论:医学影像建模。

4区计算机科学

Visual Computing for Industry, Biomedicine, and Art Pub Date : 2019-12-29 DOI: 10.1186/s42492-019-0037-2

Zhengrong Jerome Liang

引用次数: 0

Multi-scale characterizations of colon polyps via computed tomographic colonography. 通过计算机断层结肠镜检查结肠息肉的多尺度特征。

4区计算机科学

Visual Computing for Industry, Biomedicine, and Art Pub Date : 2019-12-27 DOI: 10.1186/s42492-019-0032-7

Weiguo Cao, Marc J Pomeroy, Yongfeng Gao, Matthew A Barish, Almas F Abbasi, Perry J Pickhardt, Zhengrong Liang

{"title":"Multi-scale characterizations of colon polyps via computed tomographic colonography.","authors":"Weiguo Cao, Marc J Pomeroy, Yongfeng Gao, Matthew A Barish, Almas F Abbasi, Perry J Pickhardt, Zhengrong Liang","doi":"10.1186/s42492-019-0032-7","DOIUrl":"https://doi.org/10.1186/s42492-019-0032-7","url":null,"abstract":"Texture features have played an essential role in the field of medical imaging for computer-aided diagnosis. The gray-level co-occurrence matrix (GLCM)-based texture descriptor has emerged to become one of the most successful feature sets for these applications. This study aims to increase the potential of these features by introducing multi-scale analysis into the construction of GLCM texture descriptor. In this study, we first introduce a new parameter - stride, to explore the definition of GLCM. Then we propose three multi-scaling GLCM models according to its three parameters, (1) learning model by multiple displacements, (2) learning model by multiple strides (LMS), and (3) learning model by multiple angles. These models increase the texture information by introducing more texture patterns and mitigate direction sparsity and dense sampling problems presented in the traditional Haralick model. To further analyze the three parameters, we test the three models by performing classification on a dataset of 63 large polyp masses obtained from computed tomography colonoscopy consisting of 32 adenocarcinomas and 31 benign adenomas. Finally, the proposed methods are compared to several typical GLCM-texture descriptors and one deep learning model. LMS obtains the highest performance and enhances the prediction power to 0.9450 with standard deviation 0.0285 by area under the curve of receiver operating characteristics score which is a significant improvement.","PeriodicalId":52384,"journal":{"name":"Visual Computing for Industry, Biomedicine, and Art","volume":"2 1","pages":"25"},"PeriodicalIF":0.0,"publicationDate":"2019-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s42492-019-0032-7","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37795221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9