2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)最新文献_第7页

Ultrasound Water Leakage Image Denoising By The Iterative Mmse Filter Abstract 基于迭代Mmse滤波的超声漏水图像去噪

2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2020-09-01 DOI: 10.1109/ATSIP49331.2020.9231848

M. Yahia, M. Mortula, Ameen Awwad, L. Albasha, Tarig Ali

引用次数: 0

3D Convolutional Recurrent Global Neural Network for Speech Emotion Recognition 用于语音情感识别的三维卷积递归全局神经网络

2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2020-09-01 DOI: 10.1109/ATSIP49331.2020.9231597

Baraa Zayene, Chiraz Jlassi, N. Arous

引用次数: 9

Efficient Statistical Learning Framework with Applications to Human Activity and Facial Expression Recognition 高效统计学习框架及其在人类活动和面部表情识别中的应用

2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2020-09-01 DOI: 10.1109/ATSIP49331.2020.9231759

Fatma Najar, S. Bourouis, M. Alshar'e, Roobaea Alroobaea, N. Bouguila, A. Al-Badi, Ines Channoufi

引用次数: 0

Multimodal Medical Image Registration Based on a Hybrid Optimization Strategy 基于混合优化策略的多模态医学图像配准

2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2020-09-01 DOI: 10.1109/ATSIP49331.2020.9231906

A. Daly, Hedi Yazid, B. Solaiman, N. Amara

引用次数: 1

Computerized Image Segmentation of Multiple Sclerosis Lesions Using Fuzzy Level Set Model 基于模糊水平集模型的多发性硬化症病灶计算机图像分割

2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2020-09-01 DOI: 10.1109/ATSIP49331.2020.9231765

Chaima Dachraoui, S. Labidi, A. Mouelhi

引用次数: 3

Methodologies of Audio-Visual Biometric Performance Evaluation for the H2020 SpeechXRays Project H2020语音x射线项目的视听生物识别性能评估方法

2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2020-09-01 DOI: 10.1109/ATSIP49331.2020.9231680

Aymen Mtibaa, Mohamed Amine Hmani, D. Petrovska-Delacrétaz, J. Boudy, A. Hamida, Claude Bauzou, Iacob Crucianu, I. Markopoulos, Emmanouil G Spanakis, Alexandru Nicolin, Christian Narr, M. Kockmann, Javier Pérez

{"title":"Methodologies of Audio-Visual Biometric Performance Evaluation for the H2020 SpeechXRays Project","authors":"Aymen Mtibaa, Mohamed Amine Hmani, D. Petrovska-Delacrétaz, J. Boudy, A. Hamida, Claude Bauzou, Iacob Crucianu, I. Markopoulos, Emmanouil G Spanakis, Alexandru Nicolin, Christian Narr, M. Kockmann, Javier Pérez","doi":"10.1109/ATSIP49331.2020.9231680","DOIUrl":"https://doi.org/10.1109/ATSIP49331.2020.9231680","url":null,"abstract":"Biometric recognition is nowadays widely used in different services and applications, making the user authentication easier and more secure than the traditional authentication system. Starting from this idea, the EU SpeechXRays project H2020 developed and evaluated in real-life environments a user recognition platform based on face and voice modalities. Since the proposed biometric solution was evaluated in real-life environments where biometric data recorded was not accessible because of the General Data Protection Regulation GDPR, the ground truth of the conducted evaluation was not available. To correctly report the performance evaluation, some methodologies were proposed to detect the errors caused by the absence of ground truth. This paper describes the biometric solution provided by the project and presents the biometric performance evaluation carried out in three real-life use case pilots on more than 2 000 users.","PeriodicalId":384018,"journal":{"name":"2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124205731","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

Multi-label learning embedding approach based on multi-temporal spectral signature for hyperspectral images classification 基于多时谱特征的多标签学习嵌入方法在高光谱图像分类中的应用

2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2020-09-01 DOI: 10.1109/ATSIP49331.2020.9231554

S. Hemissi, A. Alotaibi, S. Alotaibi

{"title":"Multi-label learning embedding approach based on multi-temporal spectral signature for hyperspectral images classification","authors":"S. Hemissi, A. Alotaibi, S. Alotaibi","doi":"10.1109/ATSIP49331.2020.9231554","DOIUrl":"https://doi.org/10.1109/ATSIP49331.2020.9231554","url":null,"abstract":"Currently, Hyperspectral signal processing is a crucial area of research. Respectively, various techniques have been investigated to apprehend features combination and multi-label classification issues. Indeed, significant consideration has been given to approaches supporting the use of a single type of features. Moreover, few efforts have been dedicated to model the multi-label aspect of hyperspectral pixels and to integrate simultaneously divergent kinds of interdependent features. In this paper, we propose a novel embedding multi-label learning approach integrating complementary weighted features. The proposed framework combines the singular statistical characteristics of each feature to accomplish a physically meaningful cooperative low-dimensional representation of extracted features. This will grant, in one hand, the refinement of classification process and the propagation of narrow class information to unlabeled sample, in the other hand, when only partial labeling knowledge is available. This paper makes the following contributions: (i) the extraction of multi-view features based on the 3D model of the spectral signature and (ii) an embedding multi-label based approach by better tackling unbalanced and dimensionality issues. A set of complementary spatial/spectral features is extracted in the experimental section from a series of hyperspectral images. The obtained results reflect the efficiency of the proposed classification schema while maintaining a reasonable computational complexity.","PeriodicalId":384018,"journal":{"name":"2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"208 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127598908","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

pedestrian detection for advanced driving assisting system: a transfer learning approach 高级驾驶辅助系统的行人检测:一种迁移学习方法

2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2020-09-01 DOI: 10.1109/ATSIP49331.2020.9231559

R. Ayachi, Mouna Afif, Yahia Said, Abdessalem Ben Abdelaali

引用次数: 4

Combined Optical Coherence Tomography and Ultrasound assisted analysis for retinal detachment in morning glory syndrome 联合光学相干断层扫描和超声辅助分析牵牛花综合征视网膜脱离

2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2020-09-01 DOI: 10.1109/ATSIP49331.2020.9231820

Marwa Hani, A. B. Slama, Nesrine Slokom, Hedi Trabelsi, I. Zghal, E. Sediki

{"title":"Combined Optical Coherence Tomography and Ultrasound assisted analysis for retinal detachment in morning glory syndrome","authors":"Marwa Hani, A. B. Slama, Nesrine Slokom, Hedi Trabelsi, I. Zghal, E. Sediki","doi":"10.1109/ATSIP49331.2020.9231820","DOIUrl":"https://doi.org/10.1109/ATSIP49331.2020.9231820","url":null,"abstract":"Optical imaging for biological tissue is of great interest in the biomedical field because of its many qualities. the use of the waves between the visible and the infrared makes the optical imaging noninvasive and non-destructive. The diffusion of a large part of the light propagating in such objects represents a huge handicap since a long time. The recent application of low coherence interferometry has allowed the photons of backscattered light to be selectively collected and amplified, giving rise to the technique of optical coherence tomography (OCT). this article shows the combinatorial role of OCT and ocular ultrasound in the diagnosis of morning glory syndrome disease. In Ophthalmology, follow-up after surgery is very important especially for people who expect a retinal discharge which is impossible with the OCT, so we will quote in this paper the role of ultrasound in surgery follow-up postoperative. in this context we talk about the importance of ocular ultrasound in ophthalmology and Comparing this one with the OCT technique.","PeriodicalId":384018,"journal":{"name":"2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"148 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124142852","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

Nuclei Segmentation Approach for Digestive Neuroendocrine Tumors Analysis Using optimized Color Space Conversion 基于优化颜色空间转换的消化神经内分泌肿瘤核分割分析方法

2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2020-09-01 DOI: 10.1109/ATSIP49331.2020.9231536

Hana Rmili, B. Solaiman, A. Mouelhi, R. Doghri, S. Labidi

{"title":"Nuclei Segmentation Approach for Digestive Neuroendocrine Tumors Analysis Using optimized Color Space Conversion","authors":"Hana Rmili, B. Solaiman, A. Mouelhi, R. Doghri, S. Labidi","doi":"10.1109/ATSIP49331.2020.9231536","DOIUrl":"https://doi.org/10.1109/ATSIP49331.2020.9231536","url":null,"abstract":"Microscopic examination plays a significant role in the decision making for a reliable diagnosis of digestive neuroendocrine tumors (NETs), an immunohistochemical (IHC) analysis should be conducted by pathologists in order to identify cell morphology, tissue structure, and various histological disorders. The visual and manual assessment task, performed by experts, is tedious, time-consuming, and prone to inter-observer variability. Hence, there is an urgent need for developing an automatic nuclei segmentation approach which can provide an accurate number of cancerous histological tissues and overcome the issue of overlapping cells. In the proposed study, a morphological method for microscopic image segmentation is presented, this approach is mainly based on the choice of the appropriate color space, which highlights stained cells nuclei caused by stain variability and insufficient lighting conditions. Stromal cells, that differ from tumor cells in their particular form and small size, should be removed using shape criterion. Then marker-controlled watershed technique is applied in order to reduce the over-segmentation and to detach the connected cells in the resulting images. The proposed method is compared to ground truth segmentation, the results gave a Dice score of 0.959.","PeriodicalId":384018,"journal":{"name":"2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"364 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126703725","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