Conference proceedings. IEEE International Conference on Signal and Image Processing Applications最新文献

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Analysis of Melanin Pigment Changes in Long Terms for Face of Various Ages: A Case Study on the UV Care Frequency 不同年龄面部黑色素的长期变化分析:以紫外线护理频率为例
Ikumi Nomura, Yuri Tatsuzawa, Mihiro Uchida, Nobutoshi Ojima, Takeo Imai, Keiko Ogawa, N. Tsumura
{"title":"Analysis of Melanin Pigment Changes in Long Terms for Face of Various Ages: A Case Study on the UV Care Frequency","authors":"Ikumi Nomura, Yuri Tatsuzawa, Mihiro Uchida, Nobutoshi Ojima, Takeo Imai, Keiko Ogawa, N. Tsumura","doi":"10.1007/978-3-319-94211-7_58","DOIUrl":"https://doi.org/10.1007/978-3-319-94211-7_58","url":null,"abstract":"","PeriodicalId":92495,"journal":{"name":"Conference proceedings. IEEE International Conference on Signal and Image Processing Applications","volume":"17 1","pages":"534-544"},"PeriodicalIF":0.0,"publicationDate":"2018-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75163816","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
Salient Spin Images: A Descriptor for 3D Object Recognition 显著旋转图像:三维物体识别的描述符
Jihad H'roura, Michaël Roy, A. Mansouri, D. Mammass, P. Juillion, Ali Bouzit, Patrice Méniel
{"title":"Salient Spin Images: A Descriptor for 3D Object Recognition","authors":"Jihad H'roura, Michaël Roy, A. Mansouri, D. Mammass, P. Juillion, Ali Bouzit, Patrice Méniel","doi":"10.1007/978-3-319-94211-7_26","DOIUrl":"https://doi.org/10.1007/978-3-319-94211-7_26","url":null,"abstract":"","PeriodicalId":92495,"journal":{"name":"Conference proceedings. IEEE International Conference on Signal and Image Processing Applications","volume":"22 1","pages":"233-242"},"PeriodicalIF":0.0,"publicationDate":"2018-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78186675","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: 4
Detecting Morphed Face Images Using Facial Landmarks 利用面部地标检测变形的人脸图像
U. Scherhag, Dhanesh Budhrani, M. Gomez-Barrero, C. Busch
{"title":"Detecting Morphed Face Images Using Facial Landmarks","authors":"U. Scherhag, Dhanesh Budhrani, M. Gomez-Barrero, C. Busch","doi":"10.1007/978-3-319-94211-7_48","DOIUrl":"https://doi.org/10.1007/978-3-319-94211-7_48","url":null,"abstract":"","PeriodicalId":92495,"journal":{"name":"Conference proceedings. IEEE International Conference on Signal and Image Processing Applications","volume":"106 1","pages":"444-452"},"PeriodicalIF":0.0,"publicationDate":"2018-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75020768","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: 46
Image Classification in the Frequency Domain with Neural Networks and Absolute Value DCT 基于神经网络和绝对值DCT的频域图像分类
F. Franzen
{"title":"Image Classification in the Frequency Domain with Neural Networks and Absolute Value DCT","authors":"F. Franzen","doi":"10.1007/978-3-319-94211-7_33","DOIUrl":"https://doi.org/10.1007/978-3-319-94211-7_33","url":null,"abstract":"","PeriodicalId":92495,"journal":{"name":"Conference proceedings. IEEE International Conference on Signal and Image Processing Applications","volume":"154 1","pages":"301-309"},"PeriodicalIF":0.0,"publicationDate":"2018-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79060350","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: 6
PDEs on Graphs for Image Reconstruction on Positron Emission Tomography 用于正电子发射断层成像重建的图形偏微分方程
Abdelwahhab Boudjelal, A. Elmoataz, F. Lozes, Z. Messali
{"title":"PDEs on Graphs for Image Reconstruction on Positron Emission Tomography","authors":"Abdelwahhab Boudjelal, A. Elmoataz, F. Lozes, Z. Messali","doi":"10.1007/978-3-319-94211-7_38","DOIUrl":"https://doi.org/10.1007/978-3-319-94211-7_38","url":null,"abstract":"","PeriodicalId":92495,"journal":{"name":"Conference proceedings. IEEE International Conference on Signal and Image Processing Applications","volume":"46 1","pages":"351-359"},"PeriodicalIF":0.0,"publicationDate":"2018-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83752582","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: 4
Human Dendritic Cells Segmentation Based on K-Means and Active Contour 基于k均值和活动轮廓的人类树突状细胞分割
Marwa Braiki, A. Benzinou, K. Nasreddine, A. Mouelhi, S. Labidi, N. Hymery
{"title":"Human Dendritic Cells Segmentation Based on K-Means and Active Contour","authors":"Marwa Braiki, A. Benzinou, K. Nasreddine, A. Mouelhi, S. Labidi, N. Hymery","doi":"10.1007/978-3-319-94211-7_3","DOIUrl":"https://doi.org/10.1007/978-3-319-94211-7_3","url":null,"abstract":"","PeriodicalId":92495,"journal":{"name":"Conference proceedings. IEEE International Conference on Signal and Image Processing Applications","volume":"82 1","pages":"19-27"},"PeriodicalIF":0.0,"publicationDate":"2018-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84670357","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 Novel Approach to String Instrument Recognition 一种新的弦乐器识别方法
Anushka Banerjee, Alekhya Ghosh, S. Palit, M. A. Ferrer-Ballester
{"title":"A Novel Approach to String Instrument Recognition","authors":"Anushka Banerjee, Alekhya Ghosh, S. Palit, M. A. Ferrer-Ballester","doi":"10.1007/978-3-319-94211-7_19","DOIUrl":"https://doi.org/10.1007/978-3-319-94211-7_19","url":null,"abstract":"","PeriodicalId":92495,"journal":{"name":"Conference proceedings. IEEE International Conference on Signal and Image Processing Applications","volume":"34 1","pages":"165-175"},"PeriodicalIF":0.0,"publicationDate":"2018-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88880138","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: 8
Digital Cultural Heritage Imaging via Osmosis Filtering 通过渗透过滤的数字文化遗产成像
S. Parisotto, L. Calatroni, C. Daffara
{"title":"Digital Cultural Heritage Imaging via Osmosis Filtering","authors":"S. Parisotto, L. Calatroni, C. Daffara","doi":"10.1007/978-3-319-94211-7_44","DOIUrl":"https://doi.org/10.1007/978-3-319-94211-7_44","url":null,"abstract":"","PeriodicalId":92495,"journal":{"name":"Conference proceedings. IEEE International Conference on Signal and Image Processing Applications","volume":"34 1","pages":"407-415"},"PeriodicalIF":0.0,"publicationDate":"2018-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79041701","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: 10
Fully automated esophagus segmentation with a hierarchical deep learning approach. 采用分层深度学习方法的全自动食道分割。
Conference proceedings. IEEE International Conference on Signal and Image Processing Applications Pub Date : 2017-09-01 Epub Date: 2017-12-01 DOI: 10.1109/ICSIPA.2017.8120664
Roger Trullo, Caroline Petitjean, Dong Nie, Dinggang Shen, Su Ruan
{"title":"Fully automated esophagus segmentation with a hierarchical deep learning approach.","authors":"Roger Trullo,&nbsp;Caroline Petitjean,&nbsp;Dong Nie,&nbsp;Dinggang Shen,&nbsp;Su Ruan","doi":"10.1109/ICSIPA.2017.8120664","DOIUrl":"10.1109/ICSIPA.2017.8120664","url":null,"abstract":"<p><p>Segmentation of organs at risk in CT volumes is a prerequisite for radiotherapy treatment planning. In this paper we focus on esophagus segmentation, a challenging problem since the walls of the esophagus have a very low contrast in CT images. Making use of Fully Convolutional Networks (FCN), we present several extensions that improve the performance, including a new architecture that allows to use low level features with high level information, effectively combining local and global information for improving the localization accuracy. Experiments demonstrate competitive performance on a dataset of 30 CT scans.</p>","PeriodicalId":92495,"journal":{"name":"Conference proceedings. IEEE International Conference on Signal and Image Processing Applications","volume":"2017 ","pages":"503-506"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/ICSIPA.2017.8120664","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36604209","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: 18
Keynote 2: Opportunities and challenges in hyperspectral remote sensing 主题演讲2:高光谱遥感的机遇与挑战
J. Chanussot
{"title":"Keynote 2: Opportunities and challenges in hyperspectral remote sensing","authors":"J. Chanussot","doi":"10.1109/ICSIPA.2017.8120566","DOIUrl":"https://doi.org/10.1109/ICSIPA.2017.8120566","url":null,"abstract":"Hyperspectral imagery, also called imaging spectroscopy, refers to images with a large number (typically a few hundreds) of narrow and contiguous spectral bands, covering a wide range of the electromagnetic spectrum from the visible to the infrared domain. Hyperspectral data is able to provide a very fine description of the chemical components in the sensed materials and ensure their detection, discrimination and characterization. The application of hyperspectral imagery is rapidly growing, especially in the context of space and airborne remote sensing, as well as planetary exploration and astrophysics. Additional applications include, monitoring and management of the environment, physical analysis of materials, biomedical imaging, defense and security, food safety, detection of counterfeit objects (especially in pharmacology), and precision agriculture. Unfortunately, every rose has its thorns and the price to pay for the enhanced spectral diversity is high dimensional data. The challenge is in defining appropriate signal and image processing methods. In this talk, I will review some processing and analysis techniques that explicitly handle the high dimensionality of the data, addressing various tasks, including image denoising, image segmentation, hierarchical analysis, spectral unmixing. Results will be presented on images from a variety of contexts.","PeriodicalId":92495,"journal":{"name":"Conference proceedings. IEEE International Conference on Signal and Image Processing Applications","volume":"12 1","pages":"viii"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84704669","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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