2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS)最新文献_第4页

Parallelization of digit recognition system using Deep Convolutional Neural Network on CUDA 基于CUDA的深度卷积神经网络数字识别系统并行化

2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS) Pub Date : 2017-05-01 DOI: 10.1109/SSPS.2017.8071623

Srishti Singh, Amrit Paul, M. Arun

{"title":"Parallelization of digit recognition system using Deep Convolutional Neural Network on CUDA","authors":"Srishti Singh, Amrit Paul, M. Arun","doi":"10.1109/SSPS.2017.8071623","DOIUrl":"https://doi.org/10.1109/SSPS.2017.8071623","url":null,"abstract":"A Compute Unified Device Architecture (CUDA) implementation of Deep Convolutional Neural Network (DCNN) for a digit recognition system is proposed to reduce the computation time of ANN and achieve high accuracy. A neural network with three layers of convolutions and two fully connected layers is developed by building input, hidden and output neurons to achieve an improved accuracy. The network is parallelized using a dedicated GPU on CUDA platform using Tensor flow library. A comparative analysis of accuracy and computation time is performed for sequential and parallel execution of the network on dual core (4 logical processors) CPU, octa core (16 logical processors) only CPU and octa core (16 logical processors) CPU with GPU systems. MNIST (Modified National Institute of Standards and Technology) and EMNIST (Extended MNIST) database are used for both training and testing. MNIST has 55000 training sets, 10000 testing sets and 5000 validation sets. EMNIST consists of 235000 training, 40000 testing and 5000 validation sets. The network designed requires high computation and hence parallelizing it shows significant improvement in execution time.","PeriodicalId":382353,"journal":{"name":"2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126568976","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

Digital notice board implementation via power line communication 通过电力线通信实现数字公告板

2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS) Pub Date : 2017-05-01 DOI: 10.1109/SSPS.2017.8071635

R. Ranihemamalini, S. Ashwitha, M. Aarthy, A. Abhineyaa, Aditii

引用次数: 0

Hybrid lossless and lossy compression technique for ECG signals 心电信号无损和有损混合压缩技术

2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS) Pub Date : 2017-05-01 DOI: 10.1109/SSPS.2017.8071639

Kamyar Nemati, Kannan Ramakrishnan

引用次数: 6

Hyperspectral image analysis techniques on remote sensing 遥感高光谱图像分析技术

2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS) Pub Date : 2017-05-01 DOI: 10.1109/SSPS.2017.8071626

R. P. Iyer, Archanaa Raveendran, S. Bhuvana, R. Kavitha

引用次数: 9

Extraction of single channel from mixed audio sample using adaptive factorization 利用自适应因子分解从混合音频样本中提取单通道

2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS) Pub Date : 2017-05-01 DOI: 10.1109/SSPS.2017.8071562

J. Kaur, S. Gaikwad

引用次数: 1

Classification of MRI brain tumor and mammogram images using learning vector quantization neural network 基于学习向量量化神经网络的MRI脑肿瘤和乳房x光图像分类

2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS) Pub Date : 2017-05-01 DOI: 10.1109/SSPS.2017.8071610

Ravindra Sonavane, Poonam Sonar, Surendra Sutar

引用次数: 6

The enhanced content based image retrieval system and classification of infected vegetables 基于增强内容的图像检索系统及病害蔬菜分类

2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS) Pub Date : 2017-05-01 DOI: 10.1109/SSPS.2017.8071570

N. Belsha, N. Hariprasad

{"title":"The enhanced content based image retrieval system and classification of infected vegetables","authors":"N. Belsha, N. Hariprasad","doi":"10.1109/SSPS.2017.8071570","DOIUrl":"https://doi.org/10.1109/SSPS.2017.8071570","url":null,"abstract":"Vegetables play a major role in Indian agriculture by providing economic viability, nutritional security, and fit well into the predominant intensive cropping systems prevailing in different parts of our country. To develop technologies that enhance quality and productivity of vegetables and solve increasing biotic and abiotic diseases is the major challenge in vegetable research. The vegetable disease identification and classification is the most important and catching attention research topic in the agriculture science. Image processing is the most suitable and best tool for classification and retrieval system. The Proposed work is to retrieve and classify the various types of infected and non-infected vegetable image. Searching the vegetable image from the large database for the analysis of the quality is difficult to defeat this Content-Based Image Retrieval (CBIR) system is introduced. A novel approach of CBIR system is used in the vegetable images by using feature extraction techniques. In classification of the infected vegetables is done through the process of feature extraction and classification. The final results shows for enhanced system of five types of vegetables like carrot, potato, bell pepper, Cabbage and tomato, Area of Infection of infected vegetable, and performance analysis of Infected/Non-infected vegetables.","PeriodicalId":382353,"journal":{"name":"2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121048670","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

Wideband four arm log-periodic planar antenna with Wi-Fi band rejection 具有Wi-Fi带抑制的宽带四臂对数周期平面天线

2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS) Pub Date : 2017-05-01 DOI: 10.1109/SSPS.2017.8071611

G. K. Reddy, D. Punniamoorthy, Vikram S. Kamadal, S. Srinivas

{"title":"Wideband four arm log-periodic planar antenna with Wi-Fi band rejection","authors":"G. K. Reddy, D. Punniamoorthy, Vikram S. Kamadal, S. Srinivas","doi":"10.1109/SSPS.2017.8071611","DOIUrl":"https://doi.org/10.1109/SSPS.2017.8071611","url":null,"abstract":"The log-periodic antennas (LP), also know as a log-periodic array or log-periodic aerial which are very effectively useful to achieve large bandwidth. By careful design of planar log-periodic antennas with impedance matching we get large bandwidth. The chebyshev impedance matching is one of the best techniques to produce large bandwidth in log-periodic antenna. In this paper four arm log-periodic antenna is designed for the both linear and circular polarization. When the 900 phase delay applied between the two dipoles the antenna produce circular polarization. The antenna is operated at 3GHz gives the band of operation from 2GHz band upto K/Ka band. According to IEEE 802.11 the 5.1GHz to 5.8GHz band is occupied for Wi-Fi applications. So there is a need to eliminate the Wi-Fi band by using integrating filter method. The antenna is designed and simulated by using HFSS software, the variation of voltage standing wave ratio(VSWR), return loss and axial ratio plots are generated from 2GHz to 18GHz. The antenna is fabricated on FR 4 substrate for band rejection by using integrating filter method. Measured results are well accepted with simulated results.","PeriodicalId":382353,"journal":{"name":"2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126268701","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

Analysis and classification of power quality events using Hilbert transform and fuzzy system 利用希尔伯特变换和模糊系统对电能质量事件进行分析和分类

2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS) Pub Date : 2017-05-01 DOI: 10.1109/SSPS.2017.8071604

P. Sundaram, R. Neela

引用次数: 2

Extraction of segmented vein patterns using repeated line tracking algorithm 使用重复线跟踪算法提取分段静脉模式

2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS) Pub Date : 2017-05-01 DOI: 10.1109/SSPS.2017.8071571

Bhagyashree Besra, R. Mohapatra

引用次数: 11