2018 4th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)最新文献_第7页

On the use of pitch-based features for fear emotion detection from speech 基于音高的特征在语音恐惧情绪检测中的应用

2018 4th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2018-03-21 DOI: 10.1109/ATSIP.2018.8364512

Safa Chebbi, S. B. Jebara

引用次数: 11

A compact split-ring resonator using spiral technique for UHF RFID tag 一种用于超高频RFID标签的螺旋技术的紧凑型分环谐振器

2018 4th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2018-03-21 DOI: 10.1109/ATSIP.2018.8364444

M. Abdelkarim, G. Zamora, F. Paredes, J. Bonache, F. Martín, A. Gharsallah

引用次数: 0

Target recognition in ISAR images based on relative phases of complex wavelet coefficients and sparse classification 基于复小波系数相对相位和稀疏分类的ISAR图像目标识别

2018 4th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2018-03-21 DOI: 10.1109/ATSIP.2018.8364505

Ayoub Karine, A. Toumi, A. Khenchaf, M. Hassouni

{"title":"Target recognition in ISAR images based on relative phases of complex wavelet coefficients and sparse classification","authors":"Ayoub Karine, A. Toumi, A. Khenchaf, M. Hassouni","doi":"10.1109/ATSIP.2018.8364505","DOIUrl":"https://doi.org/10.1109/ATSIP.2018.8364505","url":null,"abstract":"In this paper, we present a novel approach for radar automatic target recognition on inverse synthetic aperture radar (ISAR). This approach is composed by two complementary steps: feature extraction and recognition. For the feature extraction step, we adopt a statistical modeling of the ISAR image in the complex wavelet domain. For doing so, we apply the dual-tree complex wavelet transform (DT-CWT) for each ISAR image in the database. After that, the relative phases of the resulting complex coefficients are computed. These relative phases are after statistically modeled using the Von Mises distribution. The estimated statistical parameters compose the feature vector of the ISAR images. Regarding to the recognition rate, the constructed feature vector is fed into the sparse representation based classification (SRC). More precisely, the training feature vectors are used as the atoms of a dictionary. The test feature vector is recognized according to its sparse linear combination with the dictionary. Extensive experiments and comparisons with other methods on ISAR images database demonstrate the effectiveness of the proposed approach.","PeriodicalId":332253,"journal":{"name":"2018 4th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126157608","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

Cancelable speaker verification system based on binary Gaussian mixtures 基于二元高斯混合的可取消说话人验证系统

2018 4th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2018-03-01 DOI: 10.1109/ATSIP.2018.8364513

Aymen Mtibaa, D. Petrovska-Delacrétaz, A. Hamida

引用次数: 15

Evidence theory data fusion-based method for cyber-attack detection 基于证据理论数据融合的网络攻击检测方法

2018 4th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2018-03-01 DOI: 10.1109/ATSIP.2018.8364337

A. Dallali, Takwa Omrani, B. Rhaimi

引用次数: 3

Towards a hybrid approach for remote sensing ontology construction 面向遥感本体构建的混合方法

2018 4th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2018-03-01 DOI: 10.1109/ATSIP.2018.8364491

B. Nasri, Hafedh Nefzi, Mohamed Farah

引用次数: 4

Glioblastoma MRT exploration based on segmentation methods' comparison: Towards an advanced clinical aided tool 基于分割方法比较的胶质母细胞瘤MRT探查:迈向一种先进的临床辅助工具

2018 4th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2018-03-01 DOI: 10.1109/ATSIP.2018.8364472

Hana Bouchouicha, Olfa Ghribi, A. Hamida, C. Mhiri, M. Dammak, K. B. Mahfoudh, O. Kammoun

{"title":"Glioblastoma MRT exploration based on segmentation methods' comparison: Towards an advanced clinical aided tool","authors":"Hana Bouchouicha, Olfa Ghribi, A. Hamida, C. Mhiri, M. Dammak, K. B. Mahfoudh, O. Kammoun","doi":"10.1109/ATSIP.2018.8364472","DOIUrl":"https://doi.org/10.1109/ATSIP.2018.8364472","url":null,"abstract":"Glioblastoma delineation and its related active region specification are still a real challenge and so difficult essentially due to their multiform aspect. in fact, this type of tumors is very invasive and appears as non-enhancing region and with various forms on magnetic resonance imaging modalities. Thus, Glioblastoma segmentation is challenging especially in differentiating between white matter and edema, necrosis and gray matter due to their homogeneity in intensity and texture. An accurate delineation of the tumor is necessary for the tumor progress evaluation and medical treatment efficacy assessment. in addition, a precise limitation of the tumor is mandatory in surgical and Radio Therapies. Manual segmentation methods have been always used and require radiologist intervention and could be also used as reference. our attention was for the benefits to extract from the semi-Automatic segmentation Methods and the Fully Automatic segmentation Methods, and this would yield a real complementarity giving hence one complete and rich convivial clinical aided tool. This paper presents therefore a useful review of these methods proposed for the Glioblastoma MRI segmentation.","PeriodicalId":332253,"journal":{"name":"2018 4th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124833369","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

Leaf polarized 3-D vector RT modeling simulation based on Monte Carlo sampling 基于蒙特卡罗采样的叶片极化三维矢量RT建模仿真

2018 4th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2018-03-01 DOI: 10.1109/ATSIP.2018.8364498

A. Kallel

引用次数: 0

Comparison study for computer assisted detection and diagnosis ‘CAD’ systems dedicated to prostate cancer detection using MRImp modalities 计算机辅助检测和诊断“CAD”系统专用于前列腺癌检测使用mri模式的比较研究

2018 4th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2018-03-01 DOI: 10.1109/ATSIP.2018.8364468

A. Latrach, Rania Trigui, Hanen Chenini, Lamia Sellemi, Ben Hamida Ahmed

{"title":"Comparison study for computer assisted detection and diagnosis ‘CAD’ systems dedicated to prostate cancer detection using MRImp modalities","authors":"A. Latrach, Rania Trigui, Hanen Chenini, Lamia Sellemi, Ben Hamida Ahmed","doi":"10.1109/ATSIP.2018.8364468","DOIUrl":"https://doi.org/10.1109/ATSIP.2018.8364468","url":null,"abstract":"Prostate cancer could be considered among the leading causes of men death [1]. Prostate cancer early detection could be hence so necessary in order to confirm the existence of a tumor. It was traditionally based on conventional methods as DRE (Digital Rectal Examination), dosing Prostatic Specific Antigen (PSA) and biopsy. However, these techniques often suffer from lack of specificity, could be invasive, or linked to non-cancerous pathologies. To overcome these difficulties, it was necessary to use imaging techniques that can estimate the position, the volume, and the tumor aggressiveness. Magnetic Resonance Imaging (MRI) has emerged as a promising technique for the prostate cancer diagnosis in terms of detection and localization thanks to an excellent tissue contrast. Multi-parametric Magnetic Resonance Imaging (MRImp) was considered as a reference for detection, localization and evaluation of tumor aggressiveness. This was therefore a promising research domain to diagnose and to quickly adapt a patient monitoring. In addition, its localization capabilities help other treatment techniques, allowing local treatment of the tumor and no longer systematically resort to total removal of the gland. Computer Assisted Detection and Diagnosis systems (CAD) are intended to assist the radiologist in making decisions. We present in this paper a comparison study between the most recent CAD systems in order to clarify usefulness as well as to propose an emerging methodology for implementation that could certainly help clinicians during their diagnosis. Such a proposition was hence forth implemented and tested as one preliminary research in this promoting domain.","PeriodicalId":332253,"journal":{"name":"2018 4th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131662400","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: 3

Mammographie image based possibilistic ontological representation 基于乳房x线影像的可能性本体论表示

2018 4th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2018-03-01 DOI: 10.1109/ATSIP.2018.8364475

Yosra Ben Salem, Rihab Idoudi, K. Ettabaâ, K. Hamrouni, B. Soleiman

引用次数: 0