2017 4th International Conference on Systems and Informatics (ICSAI)最新文献_第9页

Improving the compression efficiency for transform video coding 提高变换视频编码的压缩效率

2017 4th International Conference on Systems and Informatics (ICSAI) Pub Date : 2017-11-01 DOI: 10.1109/ICSAI.2017.8248489

Jianyu Lin

引用次数: 2

Ultrasound elastography based on the normalized cross-correlation and the PSO algorithm 基于归一化互相关和粒子群算法的超声弹性成像

2017 4th International Conference on Systems and Informatics (ICSAI) Pub Date : 2017-11-01 DOI: 10.1109/ICSAI.2017.8248455

Jiaqi Wang, Qinghua Huang, Xin Zhang

引用次数: 6

Fully convolutional denoising autoencoder for 3D scene reconstruction from a single depth image 全卷积去噪自动编码器的3D场景重建从一个单一的深度图像

2017 4th International Conference on Systems and Informatics (ICSAI) Pub Date : 2017-11-01 DOI: 10.1109/ICSAI.2017.8248355

Alessandro Palla, D. Moloney, L. Fanucci

{"title":"Fully convolutional denoising autoencoder for 3D scene reconstruction from a single depth image","authors":"Alessandro Palla, D. Moloney, L. Fanucci","doi":"10.1109/ICSAI.2017.8248355","DOIUrl":"https://doi.org/10.1109/ICSAI.2017.8248355","url":null,"abstract":"In this work, we propose a 3D scene reconstruction algorithm based on a fully convolutional 3D denoising autoencoder neural network. The network is capable of reconstructing a full scene from a single depth image by creating a 3D representation of it and automatically filling holes and inserting hidden elements. We exploit the fact that our neural network is capable of generalizing object shapes by inferring similarities in geometry. Our fully convolutional architecture enables the network to be unconstrained by a fixed 3D shape, and so it is capable of successfully reconstructing arbitrary scene sizes. Our algorithm was evaluated on a real word dataset of tabletop scenes acquired using a Kinect and processed using KinectFusion software in order to obtain ground truth for network training and evaluation. Extensive measurements show that our deep neural network architecture outperforms the previous state of the art both in terms of precision and recall for the scene reconstruction task. The network has been broadly profiled in terms of memory footprint, number of floating point operations, inference time and power consumption in CPU, GPU and embedded devices. Its small memory footprint and its low computation requirements enable low power, memory constrained, real time always-on embedded applications such as autonomous vehicles, warehouse robots, interactive gaming controllers and drones.","PeriodicalId":285726,"journal":{"name":"2017 4th International Conference on Systems and Informatics (ICSAI)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116203419","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: 6

Non-stationary wiener filter design for channel estimation of PS-OFDM cognitive radio using time-reversal communication: A locally stationary approach 基于时间反转通信的PS-OFDM认知无线电信道估计的非平稳维纳滤波器设计:一种局部平稳方法

2017 4th International Conference on Systems and Informatics (ICSAI) Pub Date : 2017-11-01 DOI: 10.1109/ICSAI.2017.8248493

Munyaradzi Munochiveyi, Xiaohui Zhao, Hui Liang

{"title":"Non-stationary wiener filter design for channel estimation of PS-OFDM cognitive radio using time-reversal communication: A locally stationary approach","authors":"Munyaradzi Munochiveyi, Xiaohui Zhao, Hui Liang","doi":"10.1109/ICSAI.2017.8248493","DOIUrl":"https://doi.org/10.1109/ICSAI.2017.8248493","url":null,"abstract":"Time-reversal communication is considered as a potential Green wireless communications scheme for cognitive radio networks. The network base station utilizes time-reversal communication to exploit multi-path propagation, in order to provide spatial focusing at an intended cognitive radio. This reduces interference to other radios in the network. However, time-reversal spatial focusing performance is dependent on robust channel estimation. Under time-varying channel conditions or imperfect channel estimation, the performance of time-reversal communication deteriorates immensely. To ameliorate this deterioration, we design a non-stationary time-varying non-causal Wiener filter based on the time-varying spectrum. The time-varying spectrum is obtained by first modeling the time-varying channel as a locally stationary process. Which means that over small time intervals the channel is approximately stationary, and correlated inside these stationary intervals. Consequently, the time-varying spectrum can be easily calculated by estimating the covariance of the Wigner-Ville distribution of each locally stationary process. Based on that premise, the goal of this paper is to investigate through simulation, the performance of the proposed Wiener filter versus the conventional optimal Wiener filter when the time-varying channel is modeled as a locally stationary process. The performance is derived by computing the symbol error rate (SER), minimum mean square error (MMSE) and the output versus input signal-to-noise ratio (SNR).","PeriodicalId":285726,"journal":{"name":"2017 4th International Conference on Systems and Informatics (ICSAI)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122824916","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

Implementing neuro-adaptive control algorithms with sliding mode learning on industrial servo drives 基于滑模学习的神经自适应控制算法在工业伺服驱动器上的实现

2017 4th International Conference on Systems and Informatics (ICSAI) Pub Date : 2017-11-01 DOI: 10.1109/ICSAI.2017.8248273

N. Dimitrov, A. Topalov, Sevil A. Ahmed, Pavel Radev

{"title":"Implementing neuro-adaptive control algorithms with sliding mode learning on industrial servo drives","authors":"N. Dimitrov, A. Topalov, Sevil A. Ahmed, Pavel Radev","doi":"10.1109/ICSAI.2017.8248273","DOIUrl":"https://doi.org/10.1109/ICSAI.2017.8248273","url":null,"abstract":"The demand of the industry for high performance electric motors has significantly increased nowadays. This has boosted the usage of permanent magnet brushless synchronous motors (BLSM) in many applications where the accuracy and performance requirements are high. Further improvement of the BLSM drive systems performance can be achieved by providing them with adaptive control capabilities. The relative complexity of adaptive control schemes and algorithms and the computational load that they impose have prevented until recently their practical implementation into the industrial servo systems. In this investigation, a neuro-adaptive control scheme where the rule for parameter adaptation is designed by taking into account the variable structure control (VSC) concepts and Lyapunov stability, is proposed and embedded into an inexpensive, available on the market, position control system for brushless synchronous servomotors. The experimental tests have been carried on using compact and flexible, based on open hardware and software concept, dual-axis motion controllers PMC201/PMC202 manufactured by the PicoMotion Inc. The applied software has been written using the Motion Control Framework software platform, provided together with the above controllers. The results obtained with the proposed neuro-adaptive control scheme have been compared to those obtained using the originally built into the system PI controller. The experiments have shown that the implemented advanced adaptive control approach is practically viable and can be embedded into the industrial motion control systems which will lead to their improved performance.","PeriodicalId":285726,"journal":{"name":"2017 4th International Conference on Systems and Informatics (ICSAI)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121121716","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

Parameter analysis and selection for human gait characterization using a low cost vision system 基于低成本视觉系统的人体步态特征参数分析与选择

2017 4th International Conference on Systems and Informatics (ICSAI) Pub Date : 2017-11-01 DOI: 10.1109/ICSAI.2017.8248289

J. Ferreira, Tao Liu, Portugal Coimbra, Paulo Coimbra

{"title":"Parameter analysis and selection for human gait characterization using a low cost vision system","authors":"J. Ferreira, Tao Liu, Portugal Coimbra, Paulo Coimbra","doi":"10.1109/ICSAI.2017.8248289","DOIUrl":"https://doi.org/10.1109/ICSAI.2017.8248289","url":null,"abstract":"The main objective of this research project is to develop a low cost computerized system to automatically diagnose gait disorders and characterize their severity. The system uses 2 video cameras to provide a 3D position acquisition system connected to a personal computer. The patient gait and posture are analyzed from the data acquired by a vision-based gait acquisition system. The whole system will be an important novel tool in medical rehabilitation and diagnosis, resulting on a more effective functional rehabilitation of a patient's gait, assessing their clinical evolution and solving the limitations of the current subjective gait diagnosis tools. The system allows the calculation of 17 human gait joint trajectories. This system will provide a much more objective understanding of the patient's clinical evolution, and thus enables a more effective functional rehabilitation of a patient's gait. In this paper it is presented the selection of the relevant diagnosis parameters of the gait patterns, which is one of the steps to get to the main objective, the automatic diagnosis of human gaits.","PeriodicalId":285726,"journal":{"name":"2017 4th International Conference on Systems and Informatics (ICSAI)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121194899","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 novel dynamic Bayesian network based threat assessment algorithm 一种新的基于动态贝叶斯网络的威胁评估算法

2017 4th International Conference on Systems and Informatics (ICSAI) Pub Date : 2017-11-01 DOI: 10.1109/ICSAI.2017.8248362

Zhen-Hua Fan, Bengbeng Shi, Jin-Yong Chen, Tong-Le Duan

引用次数: 3

Standard measuring device for thickness of silicon wafer based on laser compensation system 基于激光补偿系统的硅片厚度标准测量装置

2017 4th International Conference on Systems and Informatics (ICSAI) Pub Date : 2017-11-01 DOI: 10.1109/ICSAI.2017.8248564

Yan-hua Zeng, Y. Fu, Dong-mei Tang, Yiqi Zhu

引用次数: 1

Infrared target edge detectionin in sea sky backgrand 海空背景下红外目标边缘检测

2017 4th International Conference on Systems and Informatics (ICSAI) Pub Date : 2017-11-01 DOI: 10.1109/ICSAI.2017.8248475

Shengyong Li, X. Ai, Ronghua Wu, Nianlong Zeng

引用次数: 1

Multiresolution process neural network and its learning algorithm 多分辨率过程神经网络及其学习算法

2017 4th International Conference on Systems and Informatics (ICSAI) Pub Date : 2017-11-01 DOI: 10.1109/ICSAI.2017.8248356

Y. Li, Yi An, N. Yu, Rui-bo Zhu

{"title":"Multiresolution process neural network and its learning algorithm","authors":"Y. Li, Yi An, N. Yu, Rui-bo Zhu","doi":"10.1109/ICSAI.2017.8248356","DOIUrl":"https://doi.org/10.1109/ICSAI.2017.8248356","url":null,"abstract":"A new model of multiresolution process neural network (MRPNN) which incorporates the characteristics of hierarchical, multiresolution and local learning capability is proposed based on the multiresolution analysis theory and process neural network model. This type of neural network facilitates in tackling with continuous input signals, which makes it possible to forecast time series problem. In addition, in order to approximate the nonlinear system, the hidden layer is used to deal with the nonlinear and complexity problems. A novel learning algorithm is given to expand the input functions and network weight functions based on the expansion of the orthogonal basis functions, subsequently The learning algorithm then builds the network by locating high error regions and adding nodes that get its activation function from the higher resolution space of the current local node, and its support falls within the high error region. Finally, the network is used to forecast the medium-term load of power system. Simulation results show that the network has good convergence and high accuracy. This method provides an effective solution to medium-term load forecasting in power system.","PeriodicalId":285726,"journal":{"name":"2017 4th International Conference on Systems and Informatics (ICSAI)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124151068","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