2015 The International Symposium on Artificial Intelligence and Signal Processing (AISP)最新文献_第5页

Speaker weight estimation from speech signals using a fusion of the i-vector and NFA frameworks 基于i向量和NFA框架的语音信号的说话人权重估计

2015 The International Symposium on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2015-03-03 DOI: 10.1109/AISP.2015.7123494

A. H. Poorjam, M. H. Bahari, H. Van hamme

{"title":"Speaker weight estimation from speech signals using a fusion of the i-vector and NFA frameworks","authors":"A. H. Poorjam, M. H. Bahari, H. Van hamme","doi":"10.1109/AISP.2015.7123494","DOIUrl":"https://doi.org/10.1109/AISP.2015.7123494","url":null,"abstract":"In this paper, a novel approach for automatic speaker weight estimation from spontaneous telephone speech signals is proposed. In this method, each utterance is modeled using the i-vector framework which is based on the factor analysis on Gaussian Mixture Model (GMM) mean supervectors, and the Non-negative Factor Analysis (NFA) framework which is based on a constrained factor analysis on GMM weights. Then, the available information in both Gaussian means and Gaussian weights is exploited through a feature-level fusion of the i-vectors and the NFA vectors. Finally, a least-squares support vector regression (LS-SVR) is employed to estimate the weight of speakers from given utterances. The proposed approach is evaluated on the telephone speech signals of National Institute of Standards and Technology (NIST) 2008 and 2010 Speaker Recognition Evaluation (SRE) corpora. Experimental results over 2339 utterances show that the correlation coefficients between actual and estimated weights of male and female speakers are 0.56 and 0.49, respectively, which indicate the effectiveness of the proposed method in speaker weight estimation.","PeriodicalId":405857,"journal":{"name":"2015 The International Symposium on Artificial Intelligence and Signal Processing (AISP)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126446721","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: 2

A novel video watermarking algorithm based on chaotic maps in the transform domain 一种基于变换域混沌映射的视频水印算法

2015 The International Symposium on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2015-03-03 DOI: 10.1109/AISP.2015.7123520

S. Mohammadi

引用次数: 5

An efficient content-based image retrieval with ant colony optimization feature selection schema based on wavelet and color features 一种基于小波和颜色特征的蚁群优化图像检索方法

2015 The International Symposium on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2015-03-03 DOI: 10.1109/AISP.2015.7123522

A. Rashno, S. Sadri, Hossein SadeghianNejad

引用次数: 30

Cloud authentication based on encryption of digital image using edge detection 基于边缘检测的数字图像加密云认证

2015 The International Symposium on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2015-03-03 DOI: 10.1109/AISP.2015.7123517

A. Yassin, A. Hussain, Keyan Abdul-Aziz Mutlaq

{"title":"Cloud authentication based on encryption of digital image using edge detection","authors":"A. Yassin, A. Hussain, Keyan Abdul-Aziz Mutlaq","doi":"10.1109/AISP.2015.7123517","DOIUrl":"https://doi.org/10.1109/AISP.2015.7123517","url":null,"abstract":"The security of cloud computing is the most important concerns that may delay its well-known adoption. Authentication is the central part of cloud security, targeting to gain valid users for accessing to stored data in cloud computing. There are several authentication schemes that based on username/password, but they are considered weak methods of cloud authentication. In the other side, image's digitization becomes highly vulnerable to malicious attacks over cloud computing. Our proposed scheme focuses on two-factor authentication that used image partial encryption to overcome above aforementioned issues and drawbacks of authentication schemes. Additionally, we use a fast partial image encryption scheme using Canny's edge detection with symmetric encryption is done as a second factor. In this scheme, the edge pixels of image are encrypted using the stream cipher as it holds most of the image's data and then we applied this way to authenticate valid users. The results of security analysis and experimental results view that our work supports a good balance between security and performance for image encryption in cloud computing environment.","PeriodicalId":405857,"journal":{"name":"2015 The International Symposium on Artificial Intelligence and Signal Processing (AISP)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117045127","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

Multiple soccer players tracking 多名足球运动员跟踪

2015 The International Symposium on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2015-03-03 DOI: 10.1109/AISP.2015.7123503

Nima Najafzadeh, Mehran Fotouhi, S. Kasaei

引用次数: 15

An efficient hardware implementation of few lightweight block cipher 少量轻量级分组密码的高效硬件实现

2015 The International Symposium on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2015-03-03 DOI: 10.1109/AISP.2015.7123493

Ali Nemati, S. Feizi, A. Ahmadi, Saeed Haghiri, M. Ahmadi, S. Alirezaee

{"title":"An efficient hardware implementation of few lightweight block cipher","authors":"Ali Nemati, S. Feizi, A. Ahmadi, Saeed Haghiri, M. Ahmadi, S. Alirezaee","doi":"10.1109/AISP.2015.7123493","DOIUrl":"https://doi.org/10.1109/AISP.2015.7123493","url":null,"abstract":"Radio-frequency identification (RFID) are becoming a part of our everyday life with a wide range of applications such as labeling products and supply chain management and etc. These smart and tiny devices have extremely constrained resources in terms of area, computational abilities, memory, and power. At the same time, security and privacy issues remain as an important problem, thus with the large deployment of low resource devices, increasing need to provide security and privacy among such devices, has arisen. Resource-efficient cryptographic incipient become basic for realizing both security and efficiency in constrained environments and embedded systems like RFID tags and sensor nodes. Among those primitives, lightweight block cipher plays a significant role as a building block for security systems. In 2014 Manoj Kumar et al proposed a new Lightweight block cipher named as FeW, which are suitable for extremely constrained environments and embedded systems. In this paper, we simulate and synthesize the FeW block cipher. Implementation results of the FeW cryptography algorithm on a FPGA are presented. The design target is efficiency of area and cost.","PeriodicalId":405857,"journal":{"name":"2015 The International Symposium on Artificial Intelligence and Signal Processing (AISP)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127191758","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

Integrated single image super resolution based on sparse representation 基于稀疏表示的集成单幅图像超分辨率

2015 The International Symposium on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2015-03-03 DOI: 10.1109/AISP.2015.7123523

Mehdi Khademloo, M. Rezghi

{"title":"Integrated single image super resolution based on sparse representation","authors":"Mehdi Khademloo, M. Rezghi","doi":"10.1109/AISP.2015.7123523","DOIUrl":"https://doi.org/10.1109/AISP.2015.7123523","url":null,"abstract":"This paper presents a new and efficient approach for single-image super-resolution based on sparse signal recovery. This approach uses a co-occurrence trained dictionary of image patches that obtained from a set of observed low- and high-resolution images. The linear combination of the dictionary patches can recover every patch, then each patch that used on the low-resolution image, can be recovered by the dictionary patches. Since the recovered patch is a linear combination of some patches, the noise of every patch, aggregated in the recovered patch, then we prefer a linear combination which is more sparse rather than other combinations. So the sparse representation of patches can filter the noise in the solution. Recently this approach has been used in single image super-resolution problem. These methods calculate the sparse representation of every patches separately and set it to the recovered high-resolution image. So the complexity of such methods are very high and for suitable solution the parameters of algorithm must be estimated, therefore, this process (recover all patch with an iterative algorithm and parameter estimation for each iterate) is very time consuming. This paper presents an integrated method for recovering a low-resolution image based on sparse representation of patches with one step and recover whole image together.","PeriodicalId":405857,"journal":{"name":"2015 The International Symposium on Artificial Intelligence and Signal Processing (AISP)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131640752","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: 2

Despeckling algorithm for remote sensing synthetic aperture radar images using multi-scale curvelet transform 基于多尺度曲线变换的遥感合成孔径雷达图像去斑算法

2015 The International Symposium on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2015-03-03 DOI: 10.1109/AISP.2015.7123533

M. Kooshesh, G. Akbarizadeh

{"title":"Despeckling algorithm for remote sensing synthetic aperture radar images using multi-scale curvelet transform","authors":"M. Kooshesh, G. Akbarizadeh","doi":"10.1109/AISP.2015.7123533","DOIUrl":"https://doi.org/10.1109/AISP.2015.7123533","url":null,"abstract":"The goal of the present research is to despeckle SAR images, which is critical for segmentation and target recognition in satellite SAR images. When a despeckling algorithm is applied to a SAR image, important information such as the edges, corners, textures, and object parts will degrade. Curvelet transform is a recently proposed form of multi-scale analysis that achieves better performance of wavelet and Gabor transforms in edge and curve detection. This is a geometric transform that is useful for SAR image processing. For unsupervised texture images, segmentation is different and distinct from the textures, so the textures at the boundary noises will disappear. Curvelet transform has produced good results in the detection of curved edges with higher accuracy in finding the orientation than wavelet transforms. The present study uses fast discrete curvelet transform (FDCT) based on wresting and uses unsupervised adaptive threshold learning to develop a new despeckling algorithm for SAR images. In the proposed algorithm, each segment of the SAR image can be learned for selection of its adaptive threshold. Simulation results demonstrate that the proposed algorithm performs better than similar methods.","PeriodicalId":405857,"journal":{"name":"2015 The International Symposium on Artificial Intelligence and Signal Processing (AISP)","volume":"38 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134260240","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: 2

Speech driven lips animation for the Farsi language 语音驱动的波斯语嘴唇动画

2015 The International Symposium on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2015-03-03 DOI: 10.1109/AISP.2015.7123525

Z. Naraghi, M. Jamzad

引用次数: 0

Video logo removal using iterative subsequent matching 视频logo移除使用迭代后续匹配

2015 The International Symposium on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2015-03-03 DOI: 10.1109/AISP.2015.7123495

Maryam Dashti, R. Safabakhsh, Mohammadreza Pourfard, M. Abdollahifard

引用次数: 7