2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)最新文献_第2页

Querying Data Services in an Uncertain Environment: A Possibilistic-Based Approach 不确定环境中的数据服务查询:一种基于可能性的方法

2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) Pub Date : 2016-11-28 DOI: 10.1109/SITIS.2016.47

Asma Omri, Karim Benouaret, Mohamed Nazih Omri, D. Benslimane

引用次数: 3

Selfie Detection by Synergy-Constraint Based Convolutional Neural Network 基于协同约束的卷积神经网络自拍照检测

2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) Pub Date : 2016-11-01 DOI: 10.1109/SITIS.2016.61

Yashas Annadani, Vijayakrishna Naganoor, A. Jagadish, K. Chemmangat

{"title":"Selfie Detection by Synergy-Constraint Based Convolutional Neural Network","authors":"Yashas Annadani, Vijayakrishna Naganoor, A. Jagadish, K. Chemmangat","doi":"10.1109/SITIS.2016.61","DOIUrl":"https://doi.org/10.1109/SITIS.2016.61","url":null,"abstract":"Categorisation of huge amount of data on the multimedia platform is a crucial task. In this work, we propose a novel approach to address the subtle problem of selfie detection for image database segregation on the web, given rapid rise in the number of selfies being clicked. A Convolutional Neural Network (CNN) is modeled to learn a synergy feature in the common subspace of head and shoulder orientation, derived from Local Binary Pattern (LBP) and Histogram of Oriented Gradients (HOG) features respectively. This synergy was captured by projecting the aforementioned features using Canonical Correlation Analysis (CCA). We show that the resulting network's convolutional activations in the neighbourhood of spatial keypoints captured by SIFT are discriminative for selfie-detection. In general, proposed approach aids in capturing intricacies present in the image data and has the potential for usage in other subtle image analysis scenarios apart from just selfie detection. We investigate and analyse the performance of the popular CNN architectures (GoogleNet, Alexnet), used for other image classification tasks, when subjected to the task of detecting the selfies on the multimedia platform. The results of the proposed approach are compared with these popular architectures on a dataset of ninety thousand images comprising of roughly equal number of selfies and non-selfies. Experimental results on this dataset shows the effectiveness of the proposed approach.","PeriodicalId":403704,"journal":{"name":"2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130731721","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

Fast Fully Automatic Segmentation of the Severely Abnormal Human Right Ventricle from Cardiovascular Magnetic Resonance Images Using a Multi-Scale 3D Convolutional Neural Network 基于多尺度三维卷积神经网络的心血管磁共振图像中严重异常右心室快速全自动分割

2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) Pub Date : 2016-11-01 DOI: 10.1109/SITIS.2016.16

A. Giannakidis, K. Kamnitsas, V. Spadotto, J. Keegan, Gillian Smith, B. Glocker, D. Rueckert, S. Ernst, M. Gatzoulis, D. Pennell, S. Babu-Narayan, D. Firmin

{"title":"Fast Fully Automatic Segmentation of the Severely Abnormal Human Right Ventricle from Cardiovascular Magnetic Resonance Images Using a Multi-Scale 3D Convolutional Neural Network","authors":"A. Giannakidis, K. Kamnitsas, V. Spadotto, J. Keegan, Gillian Smith, B. Glocker, D. Rueckert, S. Ernst, M. Gatzoulis, D. Pennell, S. Babu-Narayan, D. Firmin","doi":"10.1109/SITIS.2016.16","DOIUrl":"https://doi.org/10.1109/SITIS.2016.16","url":null,"abstract":"Cardiac magnetic resonance (CMR) is regarded as the reference examination for cardiac morphology in tetralogy of Fallot (ToF) patients allowing images of high spatial resolution and high contrast. The detailed knowledge of the right ventricular anatomy is critical in ToF management. The segmentation of the right ventricle (RV) in CMR images from ToF patients is a challenging task due to the high shape and image quality variability. In this paper we propose a fully automatic deep learning-based framework to segment the RV from CMR anatomical images of the whole heart. We adopt a 3D multi-scale deep convolutional neural network to identify pixels that belong to the RV. Our robust segmentation framework was tested on 26 ToF patients achieving a Dice similarity coefficient of 0.8281±0.1010 with reference to manual annotations performed by expert cardiologists. The proposed technique is also computationally efficient, which may further facilitate its adoption in the clinical routine.","PeriodicalId":403704,"journal":{"name":"2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133594600","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: 5

Times Change, Stalling Stays: Subjective Quality Assessment over Time of Stalling in Autostereoscopic 3D Video Services 时代变化，失速停留:自动立体3D视频服务中失速随时间的主观质量评估

2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) Pub Date : 2016-11-01 DOI: 10.1109/SITIS.2016.129

P. A. Kara, M. Martini, C. Hewage, F. Felisberti

引用次数: 3

The Effect of Light Field Reconstruction and Angular Resolution Reduction on the Quality of Experience 光场重建和角度分辨率降低对体验质量的影响

2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) Pub Date : 2016-11-01 DOI: 10.1109/SITIS.2016.128

P. A. Kara, P. Kovács, Suren Vagharshakyan, M. Martini, A. Barsi, T. Balogh, A. Chuchvara, Ahmed Chehaibi

引用次数: 14

Emotion Identification from Spontaneous Communication 来自自发交流的情感认同

2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) Pub Date : 2016-03-01 DOI: 10.1109/SITIS.2016.32

Fekade Getahun Taddesse, Mikiyas Kebede

{"title":"Emotion Identification from Spontaneous Communication","authors":"Fekade Getahun Taddesse, Mikiyas Kebede","doi":"10.1109/SITIS.2016.32","DOIUrl":"https://doi.org/10.1109/SITIS.2016.32","url":null,"abstract":"This study aimed to design a model for automatic identification of emotion from spontaneous communication using the acoustic characteristics of human speech. An experimental setup to collect and annotate call center Amharic telephone dialogs containing natural emotions is presented. These dialogs, involve 35 subjects (18 male and 17 female), are first manually decomposed into speaker turns and then segmented into intermediate chunks to be used as the analysis unit for feature calculation. Open class annotation is carried out by 3 professional psychologists and the various emotional states are mapped onto 4 cover classes, and a Majority Voting (MV) technique is applied to decide perceived emotion in each chunk. A total of 170 acoustic features consisting of prosodic, spectral and voice quality features are extracted from each chunk. An optimal feature set representing emotion (i.e. 33 all together) are selected through the use of generic algorithm and used to train Multilayer Perceptron Neural Network (MLPNN) classifier. A prototype application has been developed and the classification performance has been evaluated based on extracted features. Our preliminary speech emotion recognition model exhibits an average accuracy of 72.4% in identifying Anger, Fear, Positive and Sadness emotions.","PeriodicalId":403704,"journal":{"name":"2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132225708","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

Numerical Remarks on the Estimation of the Option Price 关于期权价格估计的数值说明

2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) Pub Date : 1900-01-01 DOI: 10.1109/SITIS.2016.123

S. Cuomo, R. Campagna, V. D. Somma, G. Severino

引用次数: 4

The System Vehicle of Application Detector for Categorize Type 分类型应用检测器的系统载体

2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) Pub Date : 1900-01-01 DOI: 10.1109/SITIS.2016.114

Siriruang Phatchuay, Worawut Yimyam

引用次数: 15

Equal Partition Based Clustering Approach for Event Summarization in Videos 基于等分割的视频事件摘要聚类方法

2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) Pub Date : 1900-01-01 DOI: 10.1109/SITIS.2016.27

Krishan Kumar, D. Shrimankar, Navjot Singh

{"title":"Equal Partition Based Clustering Approach for Event Summarization in Videos","authors":"Krishan Kumar, D. Shrimankar, Navjot Singh","doi":"10.1109/SITIS.2016.27","DOIUrl":"https://doi.org/10.1109/SITIS.2016.27","url":null,"abstract":"The rapid growth of video data demands both effective and efficient video summarization methods so that users are allowed to speedily browse and comprehend a large amount of video content. Hence, it is very challenging to store and access such audiovisual information in real time where an immense amount of recorded video content is rising within one second. In this paper we proposed an equal partition based clustering technique for summarizing the events in videos which can work better for real time applications (for e.g., surveillance video in various security systems). In clustering, the difficulty is to obtain the optimal set of clusters, which is gained by implementing Davies-Bouldin Index, a cluster validation technique which permits the users with free parameter based video summarization method for selecting the numbers of key–frames without incurring additional computational cost. The qualitative as well as quantitative evaluation is done in order to compare the performances of our proposed model and state-of-theart models. Experimental results on two benchmark datasets with various types of videos expose that the proposed method outperforms the state-of-the-art models with the best Precision and F–measure.","PeriodicalId":403704,"journal":{"name":"2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127332857","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: 43

Driver Drowsiness Detection Using Eye-Closeness Detection 基于眼距检测的驾驶员睡意检测

2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) Pub Date : 1900-01-01 DOI: 10.1109/SITIS.2016.110

Oraan Khunpisuth, Taweechai Chotchinasri, Varakorn Koschakosai, Narit Hnoohom

引用次数: 47