2018 Conference on Information and Communication Technology (CICT)最新文献_第8页

Manuscripts 手稿

2018 Conference on Information and Communication Technology (CICT) Pub Date : 2018-10-01 DOI: 10.1109/infocomtech.2018.8722375

引用次数: 0

Face Hallucination Techniques: A Survey 面部幻觉技术:一项调查

2018 Conference on Information and Communication Technology (CICT) Pub Date : 2018-10-01 DOI: 10.1109/INFOCOMTECH.2018.8722416

S. S. Rajput, K. V. Arya, Vinay Singh, V. Bohat

{"title":"Face Hallucination Techniques: A Survey","authors":"S. S. Rajput, K. V. Arya, Vinay Singh, V. Bohat","doi":"10.1109/INFOCOMTECH.2018.8722416","DOIUrl":"https://doi.org/10.1109/INFOCOMTECH.2018.8722416","url":null,"abstract":"In several real-world scenario, the recorded pictures often have various artifacts suchlike blur, noise, varying illuminations, occlusion, etc. due to many reasons including cheap and low-resolution imaging systems, different image processing errors, and far distance of an object from the camera/sensor. The facial images captured from such low-resolution pictures make severe impacts on the performance of various systems namely human-computer interaction, speaker recognition by mouth movements, visual speech recognition, facial expression recognition, face-recognition, etc. Facial image super-resolution (or hallucination), as one of the kernels innovations in the field of computer vision and image processing, has been an engaging but challenging technique to overcome above problems. This paper provides the comprehensive survey of existing state-of-the-art and recently published face hallucination methods. Along with this, the detailed reconstruction procedure of most successful hallucination approach i.e., position-patch based super-resolution is also provided in this work. Moreover, some useful research directions are too presented at the end which may help the research community of this filed to design and develop the new face hallucination methods for providing the more efficient solution to existing problems.","PeriodicalId":175757,"journal":{"name":"2018 Conference on Information and Communication Technology (CICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131238481","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: 11

Facial Expression Detection and Recognition using Geometry Maps 基于几何贴图的面部表情检测与识别

2018 Conference on Information and Communication Technology (CICT) Pub Date : 2018-10-01 DOI: 10.1109/INFOCOMTECH.2018.8722412

Manish P Bhatt, Monika, Parveen Kumar, Ambalika Sharma

引用次数: 3

Network Dominating Attack Detection and Mitigation 网络主导攻击检测和缓解

2018 Conference on Information and Communication Technology (CICT) Pub Date : 2018-10-01 DOI: 10.1109/INFOCOMTECH.2018.8722390

J. Johny, M. Singh

引用次数: 0

Energy Detection Spectrum Sensing on RTL-SDR based IoT Platform 基于RTL-SDR的物联网平台能量检测频谱传感

2018 Conference on Information and Communication Technology (CICT) Pub Date : 2018-10-01 DOI: 10.1109/INFOCOMTECH.2018.8722360

Saikat Majumder

引用次数: 10

Bidimensional Empirical Mode Decomposition based Intrinsically Augmented Gamma Correction for Quality Restoration of Textural Images 基于二维经验模态分解的本质增广伽玛校正纹理图像的质量恢复

2018 Conference on Information and Communication Technology (CICT) Pub Date : 2018-10-01 DOI: 10.1109/INFOCOMTECH.2018.8722388

S. V. Raghavendra Kommuri, Himanshu Singh, Anil Kumar, V. Bajaj

{"title":"Bidimensional Empirical Mode Decomposition based Intrinsically Augmented Gamma Correction for Quality Restoration of Textural Images","authors":"S. V. Raghavendra Kommuri, Himanshu Singh, Anil Kumar, V. Bajaj","doi":"10.1109/INFOCOMTECH.2018.8722388","DOIUrl":"https://doi.org/10.1109/INFOCOMTECH.2018.8722388","url":null,"abstract":"In this paper, texture and illumination improvements for the poorly acquired images are suggested with the proper restoration of images by employing content-dependent decomposition. Being a non-stationary and non-linear two-dimensional digitized signal, any image can be intrinsically decomposed according to its content and hence, content (or behavior) dependent 2-D intrinsic mode functions (2-D IMFs) can be obtained for their individual processing which collectively results into a highly efficient data restoration from the poorly acquired images. In other words, both texture and illumination based improvements can be efficiently entangled in joint space-spatial-frequency domain. Higher mode augmentation, when employed with gamma, corrected illumination boosting in an image-driven and adaptive manner leads to overall quality improvement of the textured data present in the images. In order to validate the necessity of the proposal, a rigorous experimentation is executed by employing the performance evaluation through standard quality measures and comparison with pre-existing recently proposed and highly appreciated quality enhancement approaches.","PeriodicalId":175757,"journal":{"name":"2018 Conference on Information and Communication Technology (CICT)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125993114","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

A Frequency Reconfigurable Mobile Handset Antenna for 4G and Pre-5G Technology 一种用于4G和Pre-5G技术的频率可重构手机天线

2018 Conference on Information and Communication Technology (CICT) Pub Date : 2018-10-01 DOI: 10.1109/INFOCOMTECH.2018.8722373

Arun Pant, L. Kumar, M. Parihar

引用次数: 1

Mode Analysis of Hybrid Metal-Insulator-Metal Multilayer Plasmonic Waveguide 混合金属-绝缘体-金属多层等离子体波导的模态分析

2018 Conference on Information and Communication Technology (CICT) Pub Date : 2018-10-01 DOI: 10.1109/INFOCOMTECH.2018.8722355

Pintu Kumar, D. Singh, Rakesh Ranjan

引用次数: 2

Enhanced EECP: Enhanced Energy Efficient Coverage Preserving Protocol for Heterogeneous Wireless Sensor Networks 增强型EECP:异构无线传感器网络的增强型节能覆盖保持协议

2018 Conference on Information and Communication Technology (CICT) Pub Date : 2018-10-01 DOI: 10.1109/INFOCOMTECH.2018.8722411

Sonam Maurya, V. Jain

{"title":"Enhanced EECP: Enhanced Energy Efficient Coverage Preserving Protocol for Heterogeneous Wireless Sensor Networks","authors":"Sonam Maurya, V. Jain","doi":"10.1109/INFOCOMTECH.2018.8722411","DOIUrl":"https://doi.org/10.1109/INFOCOMTECH.2018.8722411","url":null,"abstract":"In WSNs, sensor nodes are resource constrained nodes where limited energy capacity is the most crucial constraint which affects the network lifetime. In the literature, clustering is a well-known technique which helps to prolong the lifetime of the network. With respect to energy consumption, efficient cluster heads (CHs) selection advertisement and cluster formation in every round are costly within a cluster. The energy efficient coverage preserving (EECP) protocol was developed to provide efficient coverage for longer duration where new CH(s) selection advertisement and cluster formation are performed only when sink finds a better CH candidate in comparison to previously selected CH node. The hybrid routing of EECP protocol assumes single-hop communication from cluster member (CM) to CH and CH to CH/sink. But in case of large network, it is not necessary that the nearest CH/sink is within the communication range of source node. Therefore, nodes must transmit their data towards the sink in multi-hop manner. Also for CHs selection in EECP protocol, sink requires residual energy information of nodes in every round which causes rapid energy consumption of nodes in large network. To handle this issue, Enhanced EECP protocol is proposed in this paper where sink receives residual energy information only when CH’s energy goes below the certain threshold. This minimizes the energy consumption of the network to some extent. The simulation results show that proposed Enhanced EECP protocol prolongs the network and coverage lifetime by 50.35% and 157.59% respectively in comparison to EECP protocol.","PeriodicalId":175757,"journal":{"name":"2018 Conference on Information and Communication Technology (CICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130687991","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

V-SIN: Visual Saliency detection in noisy Images using convolutional neural Network V-SIN:基于卷积神经网络的噪声图像视觉显著性检测

2018 Conference on Information and Communication Technology (CICT) Pub Date : 2018-10-01 DOI: 10.1109/INFOCOMTECH.2018.8722431

Maheep Singh, Mahesh Chandra Govil, E. Pilli

{"title":"V-SIN: Visual Saliency detection in noisy Images using convolutional neural Network","authors":"Maheep Singh, Mahesh Chandra Govil, E. Pilli","doi":"10.1109/INFOCOMTECH.2018.8722431","DOIUrl":"https://doi.org/10.1109/INFOCOMTECH.2018.8722431","url":null,"abstract":"In the Computer era, the capability of a machine to differentiate salient object from the background has became a critical fact in the domain of Computer Vision. The features in the noisy images get greatly compromised, owing to which the Salient Object Detection (SOD) is difficult. Moreover, the existing research has not yet been matched the performance of humans for detecting the visual saliency in noisy environment. Therefore, this work highlights a novel SOD technique in noisy environment using convolutional neural network (CNN), while the salient object detection accuracy has been well maintained. The denoising of the image is performed using CNN which comprises the coordinate descent as a regularizing function. The performance of our proposed V-SIN technique has been assessed with four evaluation parameters, computing time, recall, precision, and F-measure on two publicly available image datasets. The experimental evaluations on these two dataset shows that the proposed model has been much robust to detect salient object in the presence of noise or mixture of noises in images.","PeriodicalId":175757,"journal":{"name":"2018 Conference on Information and Communication Technology (CICT)","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116256347","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: 1