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International Journal of Computational Vision and Robotics最新文献

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Maximum Entropy Based Semi Supervised Learning for Automatic Detection and Recognition of Objects Using Deep Convnets. 基于最大熵的半监督学习深度卷积神经网络自动检测与识别。
International Journal of Computational Vision and Robotics Pub Date : 2021-01-01 DOI: 10.1504/ijcvr.2021.10028526
Vipul Sharma, R. N. Mir
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引用次数: 0
Guidance Based Improved Depth Upsampling With Better Initial Estimate 具有更好初始估计的基于制导的改进深度上采样
International Journal of Computational Vision and Robotics Pub Date : 2020-11-18 DOI: 10.1504/ijcvr.2020.10030054
Chandra Shaker Balure, M RameshKini
{"title":"Guidance Based Improved Depth Upsampling With Better Initial Estimate","authors":"Chandra Shaker Balure, M RameshKini","doi":"10.1504/ijcvr.2020.10030054","DOIUrl":"https://doi.org/10.1504/ijcvr.2020.10030054","url":null,"abstract":"Like optical images, depth images are also gaining popularity because of its use in many applications like robot navigation, augmented reality, 3DTV and more. The commercially available depth cameras generate depth images which suffer from low spatial resolution, corrupted with noise, and missing regions. Such images need to be super-resolved, denoised and inpainted before using them to have better accuracy. Super-resolution (SR) techniques can be used to produce a high-resolution output. Since SR is an ill-posed inverse problem, a good initial estimate is always a good regulariser to find the optimal solution. We propose an initial estimate as part of our SR pipeline, esp. ×8, which will helps in quick convergence and accurate output. We propose a cascade approach by combining residual interpolation (RI) method with anisotropic total generalised variation (ATGV) method, both uses HR guidance image. The improvements are shown qualitative and quantitative with different levels of noise.","PeriodicalId":38525,"journal":{"name":"International Journal of Computational Vision and Robotics","volume":"11 1","pages":"109-125"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49107364","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
An integrative approach for path planning and tracking of shape aware mobile robot in structured environment using vision sensor 基于视觉传感器的结构化环境中形状感知移动机器人路径规划与跟踪集成方法
International Journal of Computational Vision and Robotics Pub Date : 2020-01-01 DOI: 10.1504/ijcvr.2020.10034377
Sangram Keshari Das, B. K. Rout, Sabyasachi Dash
{"title":"An integrative approach for path planning and tracking of shape aware mobile robot in structured environment using vision sensor","authors":"Sangram Keshari Das, B. K. Rout, Sabyasachi Dash","doi":"10.1504/ijcvr.2020.10034377","DOIUrl":"https://doi.org/10.1504/ijcvr.2020.10034377","url":null,"abstract":"","PeriodicalId":38525,"journal":{"name":"International Journal of Computational Vision and Robotics","volume":"1 1","pages":"1"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66728725","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
Segmentation and recognition of characters on Tulu palm leaf manuscripts 土鲁棕榈叶手稿文字的分割与识别
International Journal of Computational Vision and Robotics Pub Date : 2019-09-11 DOI: 10.1504/ijcvr.2019.10023895
P. J. Antony, C. K. Savitha
{"title":"Segmentation and recognition of characters on Tulu palm leaf manuscripts","authors":"P. J. Antony, C. K. Savitha","doi":"10.1504/ijcvr.2019.10023895","DOIUrl":"https://doi.org/10.1504/ijcvr.2019.10023895","url":null,"abstract":"This paper proposes an efficient method for segmentation and recognition of handwritten characters from Tulu palm leaf manuscript images. The proposed method uses an automated tool with a combination of thresholding and edge detection technique to binarise the image. Further projection profile with connected component analysis is used to line and character segmentation. Deep convolution neural network (DCNN) model used here to extract features and recognise segmented Tulu characters efficiently with a recognition rate of 79.92%. The results are verified using benchmark dataset, the AMADI_LontarSet to generalise our model to handwritten character recognition task. The results showed that our method outperforms from the existing state of art models.","PeriodicalId":38525,"journal":{"name":"International Journal of Computational Vision and Robotics","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73843995","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
Ethiopian Maize Diseases Recognition and Classification using: Support Vector Machine 埃塞俄比亚玉米病害识别与分类:支持向量机
International Journal of Computational Vision and Robotics Pub Date : 2019-02-27 DOI: 10.1504/IJCVR.2019.10017481
Enquhone Alehegn
{"title":"Ethiopian Maize Diseases Recognition and Classification using: Support Vector Machine","authors":"Enquhone Alehegn","doi":"10.1504/IJCVR.2019.10017481","DOIUrl":"https://doi.org/10.1504/IJCVR.2019.10017481","url":null,"abstract":"Currently, more than 72 maize diseases found in Ethiopia that attacked different part of maize. There are different traditional mechanisms to identify and classify maize leaf diseases by chemical analysis or visual observation. But, the traditional mechanisms have their own drawbacks take more time and require professional staff. Therefore, many researchers have been doing a lot in identifying and classifying the different types of diseases that attack maize using image processing. However, as far as the researcher's knowledge no attempt has been done for Ethiopian maize diseases dataset. In this study an attempt has been made to develop maize leaf diseases recognition and classification using both support vector machine model and image processing. To evaluate the recognition and classification accuracy from the total dataset of 800 images, 80% used for training and the remaining 20% for testing the model. Based on the experiment result using combined (texture, colour and morphology) features with support vector machine an average accuracy of 95.63% achieved.","PeriodicalId":38525,"journal":{"name":"International Journal of Computational Vision and Robotics","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46609010","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: 9
Effect of font size, italics, and colour count on web usability. 字体大小、斜体和颜色对网页可用性的影响。
International Journal of Computational Vision and Robotics Pub Date : 2011-04-01 DOI: 10.1504/IJCVR.2011.042271
Sanjiv K Bhatia, Ashok Samal, Nithin Rajan, Marc T Kiviniemi
{"title":"Effect of font size, italics, and colour count on web usability.","authors":"Sanjiv K Bhatia,&nbsp;Ashok Samal,&nbsp;Nithin Rajan,&nbsp;Marc T Kiviniemi","doi":"10.1504/IJCVR.2011.042271","DOIUrl":"https://doi.org/10.1504/IJCVR.2011.042271","url":null,"abstract":"<p><p>Web usability measures the ease of use of a website. This study attempts to find the effect of three factors - font size, italics, and colour count - on web usability. The study was performed using a set of tasks and developing a survey questionnaire. We performed the study using a set of human subjects, selected from the undergraduate students taking courses in psychology. The data computed from the tasks and survey questionnaire were statistically analysed to find if there was any effect of font size, italics, and colour count on the three web usability dimensions. We found that for the student population considered, there was no significant effect of font size on usability. However, the manipulation of italics and colour count did influence some aspects of usability. The subjects performed better for pages with no italics and high italics compared to moderate italics. The subjects rated the pages that contained only one colour higher than the web pages with four or six colours. This research will help web developers better understand the effect of font size, italics, and colour count on web usability in general, and for young adults, in particular.</p>","PeriodicalId":38525,"journal":{"name":"International Journal of Computational Vision and Robotics","volume":"2 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2011-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/IJCVR.2011.042271","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"31973014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 20
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