2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)最新文献

A comparative study of interworking methods among differents rats in 5G context 5G环境下不同大鼠互联方式的比较研究

2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2017-05-22 DOI: 10.1109/ATSIP.2017.8075585

Iman Zubeiri, Fatma Mrabti

引用次数: 2

Diagnosis of osteoporosis disease from bone X-ray images with stacked sparse autoencoder and SVM classifier 基于堆叠稀疏自编码器和SVM分类器的骨x线图像骨质疏松症诊断

2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2017-05-22 DOI: 10.1109/ATSIP.2017.8075537

Yassine Nasser, M. Hassouni, A. Brahim, H. Toumi, E. Lespessailles, R. Jennane

{"title":"Diagnosis of osteoporosis disease from bone X-ray images with stacked sparse autoencoder and SVM classifier","authors":"Yassine Nasser, M. Hassouni, A. Brahim, H. Toumi, E. Lespessailles, R. Jennane","doi":"10.1109/ATSIP.2017.8075537","DOIUrl":"https://doi.org/10.1109/ATSIP.2017.8075537","url":null,"abstract":"This paper focuses on the problem of osteoporosis disease diagnosis from bone X-ray images. The proposed approach takes advantage of the deep learning robustness to extract high-level features from low-level image (pixel intensities). However, the diagnosis of osteoporosis confronts two major challenges, the difficulty of distinguishing between osteoporosis and healthy subjects just from the visual inspection of bone X-ray images, and the need of a large-scale and small-size datasets for training the deep networks. In order to separate the Osteoporosis population (OP) from Control cases (CC) our proposed method performs a series of three consecutive steps, namely: 1) preprocessing to enhance the contrast of the image, 2) image subdivision with the sliding window operation and feature extraction with Staked Sparse Autoencoder (SSAE), 3) pooling operation followed by classification step using the SVM classifier. Experimental results indicate that a performance gain on classification of the two populations (OP and CC) was achieved.","PeriodicalId":259951,"journal":{"name":"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115468639","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: 16

New parallel hybrid implementation of bias correction fuzzy C-means algorithm 偏差校正模糊c均值算法的新型并行混合实现

2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2017-05-22 DOI: 10.1109/ATSIP.2017.8075519

Noureddine Ait Ali, B. Cherradi, A. Abbassi, O. Bouattane, M. Youssfi

引用次数: 5

Fission chamber's neutron signal characterization using nonnegative matrix factorization 裂变室中子信号的非负矩阵分解表征

2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2017-05-22 DOI: 10.1109/ATSIP.2017.8075522

H. Arahmane, R. Moursli, E. Hamzaoui

引用次数: 8

End-to-end system for printed Amazigh script recognition in document images 端到端系统打印Amazigh脚本识别在文档图像

2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2017-05-22 DOI: 10.1109/ATSIP.2017.8075520

N. Aharrane, A. Dahmouni, K. E. Moutaouakil, K. Satori

引用次数: 2

Using input delay approach for synthesizing an anti-windup compensator to AQM in TCP/IP networks 采用输入延迟方法合成TCP/IP网络中AQM的抗绕组补偿器

2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2017-05-22 DOI: 10.1109/ATSIP.2017.8075573

Ouarda Lamrabet, N. Fezazi, F. E. Haoussi, E. Tissir

引用次数: 28

Power budget analysis for a LEO polar orbiting nano-satellite 低轨道极轨纳米卫星功率预算分析

2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2017-05-22 DOI: 10.1109/ATSIP.2017.8075580

S. Dahbi, A. Aziz, S. Zouggar, M. E. Hafyani, Oujda Morocco, A. Hanafi, M. Karim, I. Latachi, T. Rachidi

引用次数: 11

Affinity propagation for unsupervised classification of remotely sensed images 基于亲和传播的遥感图像无监督分类

2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2017-05-22 DOI: 10.1109/ATSIP.2017.8075579

A. Tahraoui, R. Khedam, A. Bouakache, A. B. Aissa

{"title":"Affinity propagation for unsupervised classification of remotely sensed images","authors":"A. Tahraoui, R. Khedam, A. Bouakache, A. B. Aissa","doi":"10.1109/ATSIP.2017.8075579","DOIUrl":"https://doi.org/10.1109/ATSIP.2017.8075579","url":null,"abstract":"The aim of this paper is to present a new unsupervised classification method for satellite multispectral images based on affinity propagation (AP) algorithm. Recently proposed, affinity propagation becomes the most widely methods for data clustering. This technique is essentially based on passing of messages between pixels to be automatically classified without any a priori knowledge about the number of classes. Its main advantage is that initially all pixels to classify are considered as centroids or “exemplars”. However, the AP method has two major drawbacks: 1) when it comes to partition multispectral images of high spatial size, complexity of computation becomes quadratic 2) it gives an overestimation of class number due to its great sensitivity to very small variations in the image. In this work, we present the AP algorithm in its original version and we have proposed an iterative AP-block procedure to address the two issues mentioned above. Both versions have been applied to classify a low spatial resolution image acquired by ETM+ sensor of american satellite LandSat-7. From obtained results, it is concluded that the proposed AP-block classifier is more appropriate and more efficient to unsupervised image classification than the classical AP algorithm.","PeriodicalId":259951,"journal":{"name":"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121517311","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

Novel approach for quality enhancement of Arabic text to speech synthesis 提高阿拉伯语文本语音合成质量的新方法

2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2017-05-22 DOI: 10.1109/ATSIP.2017.8075550

Oumaima Zine, A. Meziane

{"title":"Novel approach for quality enhancement of Arabic text to speech synthesis","authors":"Oumaima Zine, A. Meziane","doi":"10.1109/ATSIP.2017.8075550","DOIUrl":"https://doi.org/10.1109/ATSIP.2017.8075550","url":null,"abstract":"Text To Speech technologies are widely being used in applications to help users with special needs such as blind, deafened, individuals with severe speech impairments and dyslexics. In this context particular focus has been given by the Text To Speech (TTS) researchers to achieve a high level of intelligibility for many languages such as French and English. However, Arabic TTS is still in its early development stages and needs to be improved to reach high quality. In this paper, we describe a novel concatenative approach based on lemma and Arabic patterns. Moreover, an alternative method for synthesizing diacritized Arabic texts is proposed and adopted, using a set of sub-segments where the consonant is considered as the nucleus of the acoustic unit, and hence this latter is taken with its vocalic context. This speech unit consists of half vowel-Consonant-Half vowel, adapted to the different positions in the word (Initial, medial and final). A reduction process of the resulted combinations of the proposed acoustic units will also be described in this work, in order to reduce the theoretical number of the generated sub-segment models. Furthermore, a speech corpora design for Arabic Text To Speech (ATTS) based on pre-recorded Audiobooks from Masmoo3 Audiobooks website, is presented. The corpus contains more than 4 hours of a continuous speech of Modern Standard Arabic (MSA) recorded in high intelligibility and providing phonetically balanced sentences. The proposed approach was evaluated using the Diagnostic Rhyme Test (DRT) that measures the intelligibility of the synthesized speech on the word-level. The sentence-level test was also conducted. The results of the both tests are illustrated in the experiments and results section.","PeriodicalId":259951,"journal":{"name":"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"59 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116571445","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

Speaker identification: A way to reduce call-sign confusion events 说话人识别:一种减少呼号混淆事件的方法

2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2017-05-22 DOI: 10.1109/ATSIP.2017.8075593

Sara Sekkate, Mohammed Khalil, A. Adib

{"title":"Speaker identification: A way to reduce call-sign confusion events","authors":"Sara Sekkate, Mohammed Khalil, A. Adib","doi":"10.1109/ATSIP.2017.8075593","DOIUrl":"https://doi.org/10.1109/ATSIP.2017.8075593","url":null,"abstract":"This paper examines the development of a speaker identification system (SIS) for future aeronautical communication systems. SIS promises to improve flight safety by reducing the incidence of call-sign confusion events. However, the practical development of such a system faces many challenges, especially related to the signal corruption by the channel noise. Due to the dynamic motion of aircraft, the aeronautical channel experiences high Doppler shifts and fading due to multipath propagation. This means that the SIS is required to be robust against such perturbations. In the proposed system, aeronautical channel noise was generated and mixed with speech signals to get the testing data. Four spectral features including Linear Predictive Cepstral Coefficients (LPCC), Perceptual Linear Prediction (PLP), Mel Frequency Cepstral Coefficient (MFCC) and Gammatone Frequency Cepstral Coefficient (GFCC) were extracted and then Support Vector Machines (SVM) were used for classification. The performance of the system was evaluated using noiseless and noisy signals from the ATCOSIM speech corpus. The experimental results show that the better recognition rate is obtained for GFCC under noisy conditions as compared to PLP, LPCC and MFCC.","PeriodicalId":259951,"journal":{"name":"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129719857","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