{"title":"Consolidating Product Spectrum and Gammatone filterbank for robust speaker verification under noisy conditions","authors":"M. Fedila, Messaoud Bengherabi, A. Amrouche","doi":"10.1109/ISDA.2015.7489252","DOIUrl":"https://doi.org/10.1109/ISDA.2015.7489252","url":null,"abstract":"Motivated by recent advances in speech and audio processing community reporting that incorporating the phase information can improve further the performance of state-of-the-art phase-independent features. We propose in this paper a modification in the extraction pipeline of the Mel-frequency Product Spectrum Cepstral Coefficients MFPSCC which warp the product spectrum with a Mel- Scale filterbank. The main novelty of this work resides in incorporating a Gammatone filterbank as a substitute of the Mel filterbank to reinforce the robustness of whole speaker verification system in noisy conditions. The proposed feature is dubbed the Gammatone Product-Spectrum Cepstral coefficients GPSCC. Experimental results are undertaken on the TIMIT corpus corrupted by different stationary and non-stationary noises using the GMMUBM de facto standard for speaker verification. Performance evaluations demonstrate drastic reduction in Equal Error Rates when using GPSCC compared to other related features and this gain in performance is more pronounced at low signal to noise ratios.","PeriodicalId":196743,"journal":{"name":"2015 15th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131628418","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}
{"title":"ANOFS: Automated negotiation based online feature selection method","authors":"F. B. Said, A. Alimi","doi":"10.1109/ISDA.2015.7489229","DOIUrl":"https://doi.org/10.1109/ISDA.2015.7489229","url":null,"abstract":"Feature selection is an important technique in machine learning and pattern classification. Most existing studies of feature selection are using the batch learning methods. Such methods are not appropriate for real-world applications especially when data arrive sequentially. Recently, this problem is addressed by some feature selection techniques using online learning. Despite the advantages in efficiency of online feature selection methods, they are not always accurate enough when handling real world data. In this paper, we address this limitation by the integration of automated negotiation process. We present a novel method based on negotiation theory for online feature selection (ANOFS) and demonstrate its application to several public datasets.","PeriodicalId":196743,"journal":{"name":"2015 15th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131702019","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}
{"title":"Object detection and identification for blind people in video scene","authors":"Hanen Jabnoun, F. Benzarti, H. Amiri","doi":"10.1109/ISDA.2015.7489256","DOIUrl":"https://doi.org/10.1109/ISDA.2015.7489256","url":null,"abstract":"Vision is one of the very essential human senses and it plays the most important role in human perception about surrounding environment. Hence, over thousands of papers have been published on these subjects that propose a variety of computer vision products and services by developing new electronic aids for the blind. This paper aims to introduce a proposed system that restores a central function of the visual system which is the identification of surrounding objects. This method is based on the local features extraction concept. The simulation results using SFIT algorithm and keypoints matching showed good accuracy for detecting objects. Thus, our contribution is to present the idea of a visual substitution system based on features extractions and matching to recognize and locate objects in images.","PeriodicalId":196743,"journal":{"name":"2015 15th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132262208","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}
{"title":"Deep neural network with RBF and sparse auto-encoders for numeral recognition","authors":"D. Mellouli, T. M. Hamdani, A. Alimi","doi":"10.1109/ISDA.2015.7489160","DOIUrl":"https://doi.org/10.1109/ISDA.2015.7489160","url":null,"abstract":"In this paper we proposed a new deep neural network architecture which is composed from a radial basis function neural network (RBF NN) followed by two auto-encoders and softmax classifier and we presented some comparison between this architecture and other architecture on numeral recognition applications. We gave also a review about RBF and sparse auto-encoder neural networks in the literature. First we defined neural networks and their different type's especially radial basis function neural networks (RBF NN) due to their specificity. Second we focused on auto-encoders and sparse coding then we moved to sparse auto-encoders and finally we demonstrated the effectiveness of our deep architecture by showing our experimental results and some comparisons.","PeriodicalId":196743,"journal":{"name":"2015 15th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127816484","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}
Hanen Abbes, K. Loukil, Hafedh Abid, M. Abid, Ahmad Toumi
{"title":"Implementation of a Maximum Power Point Tracking fuzzy controller on FPGA circuit for a photovoltaic system","authors":"Hanen Abbes, K. Loukil, Hafedh Abid, M. Abid, Ahmad Toumi","doi":"10.1109/ISDA.2015.7489260","DOIUrl":"https://doi.org/10.1109/ISDA.2015.7489260","url":null,"abstract":"Owing to the complexity of photovoltaic systems and their specific behavior, researchers are substantially prompted by the FPGA circuit for prototyping and testing photovoltaic system. In addition, to improve the efficiency of the photovoltaic system, Maximum Power Point Tracking (MPPT) is an essential technique that enables photovoltaic panel delivers its maximum output power. Fuzzy logic technique seems to be an efficient solution that ensures optimal operation of photovoltaic system. For this end, this work aim to implement a fuzzy logic MPPT technique on FPGA circuit to control a photovoltaic system. The system composed of photovoltaic panel, boost converter and the fuzzy logic controller using FPGA device to control boost converter switch is designed and implemented. Simulation results exhibit an efficient operation of FPGA based photovoltaic system.","PeriodicalId":196743,"journal":{"name":"2015 15th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124583480","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}
{"title":"A new Motion Estimation technique for Video Coding","authors":"Mahmoudreza Ahmadi, A. Wali, A. Walha, A. Alimi","doi":"10.1109/ISDA.2015.7489210","DOIUrl":"https://doi.org/10.1109/ISDA.2015.7489210","url":null,"abstract":"Personal wireless communication and digital multimedia information devices become widely available and extensively used. These devices require more and more developed video codecs. Hence, several video coding standards motivate developers to innovate and improve them. The block of Motion Estimation (ME) is an important module in all recent video coders. This paper presents REGIM Video Coding (REGIM-VC) as a new video coding technique. REGIM-VC proposes an efficient motion estimation algorithm based on block matching. The proposed algorithm purpose is to improve the compression performance by applying new Motion Estimation techniques. For this reason, it reduces the search points number in Motion Estimation block of video codec. Consequently, it saves significantly the bit-rate and the computational time.","PeriodicalId":196743,"journal":{"name":"2015 15th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114570386","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}
Tiia Ikonen, I. Pöllänen, Billy Braithwaite, Keijo Haataja, Pekka J. Toivanen, T. Tolonen, J. Isola
{"title":"Morphological extraction of cancerous nucleus in the diagnostics of breast cancer","authors":"Tiia Ikonen, I. Pöllänen, Billy Braithwaite, Keijo Haataja, Pekka J. Toivanen, T. Tolonen, J. Isola","doi":"10.1109/ISDA.2015.7489216","DOIUrl":"https://doi.org/10.1109/ISDA.2015.7489216","url":null,"abstract":"In this paper, cancerous nucleus is studied from the morphological point of view with focus on the analysis of anisonucleosis, nuclear deformity, hyperchromasia, and nucleocytoplasmic ratio with CAD-based (Computer Assisted Diagnosis) solutions. Mathematical Morphology (MM), more specifically Top-Hat Transform is used together with RGB color channel manipulation to process the histopathologic image to detect and extract nuclei for further analysis. Some preliminary results are presented and they seem to be quite promising in the extraction of nuclei area. The separation of nuclei from other tissue sections is the key component in the analysis of cancerous tissues. Moreover, we will present some new ideas that will be used in our future research work.","PeriodicalId":196743,"journal":{"name":"2015 15th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114379809","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}
{"title":"Toward an optimal medical image compression based on ISOM","authors":"I. Chaabouni, M. Bouhlel","doi":"10.1109/ISDA.2015.7489268","DOIUrl":"https://doi.org/10.1109/ISDA.2015.7489268","url":null,"abstract":"Images require substantial storage and transmission resources, thus image compression is advantageous to reduce these requirements. A good strategy of pictures compression should assure a good compromise between a high compression rate and a low distortion of the picture. In this paper, we present a direct solution method based on incremental self organizing map (ISOM) and discrete wavelet transform (DWT) for image compression. This method is a combination of DWT decomposition and ISOM image compression. Wavelet transform is applied to medical ultrasound images, so it produces no blocking artefacts; this is a major advantage of wavelet over other transform methods. In fact, we apply a lossless codec for approximation coefficients and ISOM for horizontal, vertical and diagonal coefficients. The results show that the proposed approach for medical ultrasound image succeeded to improve high performances in terms of compression ratio and reconstruction quality compared to JPEG image compression.","PeriodicalId":196743,"journal":{"name":"2015 15th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117044943","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}
{"title":"Improved recurrent neural network architecture for SVM learning","authors":"Rahma Fourati, C. Aouiti, A. Alimi","doi":"10.1109/ISDA.2015.7489221","DOIUrl":"https://doi.org/10.1109/ISDA.2015.7489221","url":null,"abstract":"In this paper, we provide an improvement of the circuit implementation of a one-layer recurrent neural network for support vector machine learning in pattern classification and regression. Our goal is to reduce the complexity of this architecture. Numerical example with graphical illustration is given to illuminate our main results.","PeriodicalId":196743,"journal":{"name":"2015 15th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123960038","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}
{"title":"GPU-based segmentation of dental X-ray images using active contours without edges","authors":"Ramzi Ben Ali, R. Ejbali, M. Zaied","doi":"10.1109/ISDA.2015.7489167","DOIUrl":"https://doi.org/10.1109/ISDA.2015.7489167","url":null,"abstract":"Image data is of immense practical importance in medical informatics. In teeth-related radiograph research, the information of teeth shape is the most critical factor for achieving highly automated diagnosis. Automated image segmentation, which aims at automated extraction of region boundary features, plays a fundamental role in understanding image content for searching and mining in medical image. Therefore, accurate segmentation is an essential but difficult task due to low contrast between regions of interest and uneven exposure of the dental X-ray image. To address this problem, several segmentation approaches have been proposed in the literature, with many of them providing rather promising results. In this paper, we will look at a model by Chan-Vese that detects objects not defined by gradient. We will then implement this algorithm on the GPU and see what kind of speedup we can get compared to serial CPU implementations. Finally we will quantity our results as well as make a qualitative evaluation of the method with respect to how it performs for segmenting medical images.","PeriodicalId":196743,"journal":{"name":"2015 15th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"151 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125885779","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}