2016 Twenty Second National Conference on Communication (NCC)最新文献_第10页

Two elements dual segment cylindrical dielectric resonator antenna array with annular shaped microstrip feed 带环形微带馈电的双单元双段圆柱形介质谐振器天线阵列

2016 Twenty Second National Conference on Communication (NCC) Pub Date : 2016-03-01 DOI: 10.1109/NCC.2016.7561168

Gourab Das, Anand Sharma, R. Gangwar

引用次数: 3

Multiresolution inter-sample and inter-lead eigen error features for classification of cardiac diseases 用于心脏疾病分类的多分辨率样本间和导联间特征误差特征

2016 Twenty Second National Conference on Communication (NCC) Pub Date : 2016-03-01 DOI: 10.1109/NCC.2016.7561157

R. Tripathy, S. Dandapat

引用次数: 2

Reduced dimension superimposed precoder feedback for interference alignment 降维叠加预编码器反馈干涉对准

2016 Twenty Second National Conference on Communication (NCC) Pub Date : 2016-03-01 DOI: 10.1109/NCC.2016.7561131

Navneet Garg, G. Sharma

引用次数: 4

Improved acoustic modeling of low-resource languages using shared SGMM parameters of high-resource languages 利用高资源语言的共享SGMM参数改进低资源语言的声学建模

2016 Twenty Second National Conference on Communication (NCC) Pub Date : 2016-03-01 DOI: 10.1109/NCC.2016.7561169

N. M. Joy, B. Abraham, K. Navneeth, S. Umesh

引用次数: 1

An efficient face model for facial expression recognition 一种高效的面部表情识别模型

2016 Twenty Second National Conference on Communication (NCC) Pub Date : 2016-03-01 DOI: 10.1109/NCC.2016.7561187

Sunil Kumar, M. Bhuyan, B. Chakraborty

{"title":"An efficient face model for facial expression recognition","authors":"Sunil Kumar, M. Bhuyan, B. Chakraborty","doi":"10.1109/NCC.2016.7561187","DOIUrl":"https://doi.org/10.1109/NCC.2016.7561187","url":null,"abstract":"Existing facial expression recognition (FER) algorithms aim to extract discriminative features from a face. These discriminative features can be extracted only from the informative regions of a face. In this view, several face models are proposed which are mainly intended to extract geometrical features from a face, and hence these models may not be suitable for extract discriminative texture features from a face. We proposed a novel face model based on projection analysis of a face. Our proposed projection analysis evaluates the distribution of informative regions of a face. This is done by projecting the expressive face images onto their corresponding neutral images. Hence, the proposed face model can efficiently extract distinctive texture features from a face. Additionally, the proposed face model can extract geometrical features as well. The performance of the proposed face model is evaluated on MUG datasets which shows that the proposed face model outperforms several existing face models. Also, the proposed face model can give a recognition accuracy of 97.3% which is significantly better than the performance of state-of-the-art face models.","PeriodicalId":279637,"journal":{"name":"2016 Twenty Second National Conference on Communication (NCC)","volume":"1 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":"130090009","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: 4

Arbitrary beamforming based FSO MIMO system in atmospheric turbulence and misalignment errors 基于任意波束形成的FSO MIMO系统在大气湍流和失调中的应用

2016 Twenty Second National Conference on Communication (NCC) Pub Date : 2016-03-01 DOI: 10.1109/NCC.2016.7561167

P. Sharma, Ankur Bansal, M. Bhatnagar

引用次数: 3

Image quality assessment for a selective-processing noise-aided iterative enhancement algorithm 一种选择性处理噪声辅助迭代增强算法图像质量评价

2016 Twenty Second National Conference on Communication (NCC) Pub Date : 2016-03-01 DOI: 10.1109/NCC.2016.7561114

R. Chouhan, P. Biswas

{"title":"Image quality assessment for a selective-processing noise-aided iterative enhancement algorithm","authors":"R. Chouhan, P. Biswas","doi":"10.1109/NCC.2016.7561114","DOIUrl":"https://doi.org/10.1109/NCC.2016.7561114","url":null,"abstract":"This paper presents a revision of the existing universal image quality index (UIQ) metric in order to gauge the quality of images in a selective-processing iterative enhancement algorithm. The original UIQ is based on factors of loss of correlation, luminance and contrast similarity, and is, therefore, unsuitable in enhancement-related applications. While testing existing state-of-the-art metrics as image quality criterion in an iterative dynamic range compression algorithm, a lack of coherence was observed between the objective scores and that obtained from subjective evaluation study with twenty human subjects. We, therefore, propose to modify the existing UIQ with properties of a tone-mapped image. The proposed variant, named image quality metric for dynamic range compression, IQDRC, maintains the contributing effect of structural correlation and local contrast similarity, but observes an inverse relation with local luminance similarity. The proposed metric was observed to promisingly quantify the image quality and dynamic range compression of such images in close accordance with subjective scores for the target enhancement algorithm. Observations also suggest that IQDRC is indicative of image quality for various other dynamic range compression algorithms.","PeriodicalId":279637,"journal":{"name":"2016 Twenty Second National Conference on Communication (NCC)","volume":"6 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":"115170614","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

Reliable tempo detection for structural segmentation in sarod concerts 可靠的节奏检测结构分割在sarod音乐会

2016 Twenty Second National Conference on Communication (NCC) Pub Date : 2016-03-01 DOI: 10.1109/NCC.2016.7561163

T. P. Vinutha, Suryanarayana Sankagiri, P. Rao

引用次数: 6

Exploring different acoustic modeling techniques for the detection of vowels in speech signal 探索语音信号中元音检测的不同声学建模技术

2016 Twenty Second National Conference on Communication (NCC) Pub Date : 2016-03-01 DOI: 10.1109/NCC.2016.7561195

Avinash Kumar, S. Shahnawazuddin, G. Pradhan

{"title":"Exploring different acoustic modeling techniques for the detection of vowels in speech signal","authors":"Avinash Kumar, S. Shahnawazuddin, G. Pradhan","doi":"10.1109/NCC.2016.7561195","DOIUrl":"https://doi.org/10.1109/NCC.2016.7561195","url":null,"abstract":"In this paper, we explore acoustic modeling techniques based on the Gaussian mixture modeling (GMM), the subspace GMM (SGMM) and deep neural network (DNN) for the detection of vowels in a given speech signal. At the outset, we develop a recognition system on the TIMIT database that recognizes the sequence of phonetic units present in a given speech sample. Two recognizers are developed using speech data sampled at 16 kHz and 8 kHz rates, respectively. The phone error rates (classification errors) for the two recognizers help in studying the effect of sampling rate on the classifier performance. The experimental evaluations presented in this study show that there is a slight deterioration in the recognition performance when speech data is re-sampled to 8 kHz rate. Next, a three-class classifier (vowel, non-vowel and silence) is also developed on the TIMIT database and the classification performances are studied. Using the three-class classifier, a given speech sample is then forced aligned against the trained acoustic model under the constraints of true/first-pass transcriptions to detect the vowel regions. The correctly detected and spurious vowel regions are analyzed in detail to find the impact of semivowel and nasal sound units on the detection of vowel regions as well as on the determination of vowel onset and end points. Among the explored acoustic modeling techniques, the SGMM-based system is observed to superior to all other systems. Furthermore, for all the studied modeling techniques, the spurious cases are mostly due to the detection of semivowels as the vowels.","PeriodicalId":279637,"journal":{"name":"2016 Twenty Second National Conference on Communication (NCC)","volume":"1 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":"115470463","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: 13

Multi character frequency based encoding for efficient text messaging in Indian Languages 基于多字符频率的印度语高效短信编码

2016 Twenty Second National Conference on Communication (NCC) Pub Date : 2016-03-01 DOI: 10.1109/NCC.2016.7561128

Manu Seth, Sourya Basu, Shivam Chaturvedi, R. Hegde

{"title":"Multi character frequency based encoding for efficient text messaging in Indian Languages","authors":"Manu Seth, Sourya Basu, Shivam Chaturvedi, R. Hegde","doi":"10.1109/NCC.2016.7561128","DOIUrl":"https://doi.org/10.1109/NCC.2016.7561128","url":null,"abstract":"Short Message Service (SMS) via cell phones is a widely used mode of data communication. Currently employed encoding schemes allow the transmission of 160 characters per SMS in English. This drops to 70 characters per SMS if any Indian language including Hindi is used, due to the UNICODE format used therein. Schemes proposed to improve the encoding efficiency of short text messaging generally encode one character at a time. Table splitting schemes that reduce the average number of bits per character are generally used in this context. In this paper, a novel multi-character frequency-based encoding scheme is proposed for efficient messaging of short text messages in four Indian Languages. Both uni-gram and bi-gram modelling based schemes are proposed herein. The efficiency of the proposed schemes is evaluated by conducting experiments on a large multilingual database of short text messages collected from twitter using a dictionary learning approach. Performance evaluation shows that these encoding schemes can allow the transmission of around 190 characters per SMS in English and more than 165 characters per SMS for Four Indian Languages. Encoding efficiency is significantly improved when compared to existing state of the art table marker algorithms and is motivating enough to be used in practice for transmission of short text messages in Indian Languages.","PeriodicalId":279637,"journal":{"name":"2016 Twenty Second National Conference on Communication (NCC)","volume":"28 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":"127723281","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