2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA)最新文献

A neural network based place recognition technique for a crowded indoor environment 基于神经网络的室内拥挤环境位置识别技术

2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA) Pub Date : 2017-06-20 DOI: 10.1109/ICIEA.2017.8283155

A. Perera, Ravindra Ranasinghe, G. Dissanayake

{"title":"A neural network based place recognition technique for a crowded indoor environment","authors":"A. Perera, Ravindra Ranasinghe, G. Dissanayake","doi":"10.1109/ICIEA.2017.8283155","DOIUrl":"https://doi.org/10.1109/ICIEA.2017.8283155","url":null,"abstract":"Place recognition in a crowded and cluttered environment is a challenging task due to its dynamic characteristics such as moving obstacles, varying lighting conditions and occlusions. This work presents a robust place recognition technique that could be applied into a similar environment, by combining well known Bag of Words technique with a feedforward neural network. The feedforward neural network we use have three layers with a single hidden layer and it relies on rectifier and softmax activation functions. We employ cross entropy function to model the cost of our neural network and utilize Adam algorithm for minimizing this cost at the training phase. The output layer with softmax activation in the neural network, produces a vector of probabilities which represent the likelihood of test image being captured from a given region. These values are further improved by incorporating a transition matrix which is based on the building layout. We have evaluated our neural network based place recognition technique with data collected from a crowded indoor shopping mall and promising results have been observed by this approach. We also have analyzed the behavior of neural network for changes in hyper-parameters and presented the results.","PeriodicalId":443463,"journal":{"name":"2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131984615","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

An evolutionary algorithm with 2-D encoding for image segmentation 基于二维编码的图像分割进化算法

2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA) Pub Date : 2017-06-20 DOI: 10.1109/ICIEA.2017.8283134

Miao Zhang, Huiqi Li, S. Su

{"title":"An evolutionary algorithm with 2-D encoding for image segmentation","authors":"Miao Zhang, Huiqi Li, S. Su","doi":"10.1109/ICIEA.2017.8283134","DOIUrl":"https://doi.org/10.1109/ICIEA.2017.8283134","url":null,"abstract":"This paper presents an evolutionary approach which treats the image segmentation as a graph partitioning problem. An image is described as a weighted undirected graph where pixels correspond to nodes, and those pixels with similar values and positions are connected by edges. The weighted normalized cut criterion (WNcut) is used in this paper for this graph partitioning problem to measures both the dissimilarity between different partitions and the total similarity within the groups. This paper adopts a 2-dimensional representation of chromosome to directly present an image segmentation which is beneficial both to the genetic operators in the evolutionary process and to efficiently reduce the running time. In addition, the proposed evolutionary algorithm uses prior user's preference information to control the segments of the image through a random walker approach to initialize population. Experimental results demonstrate that our proposed algorithm is able to efficiently handle segmentation cases that segments images into several partitions based on human visual perception. The statistical results of entropy-based evaluation also suggest that our approach could achieve a more accurate segmentation.","PeriodicalId":443463,"journal":{"name":"2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126459931","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

Effects of switching frequency and motor speed on common mode voltage, common mode current and shaft voltage in PWM inverter-fed induction motors 开关频率和电机转速对PWM逆变式异步电动机共模电压、共模电流和轴电压的影响

2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA) Pub Date : 2017-06-18 DOI: 10.1109/ICIEA.2017.8282911

T. G. Arora, M. Renge, M. Aware

引用次数: 19

Agent-based modeling and simulation of a small scale cyber-physical system using NetLogo 基于agent的小型网络物理系统的NetLogo建模与仿真

2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA) Pub Date : 2017-06-18 DOI: 10.1109/ICIEA.2017.8282968

J. Barbosa, P. Leitão

引用次数: 2

Optimization of rotor blade in stage circumstance for transonic axial flow compressor 跨声速轴流压气机级环境动叶优化

2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA) Pub Date : 2017-06-18 DOI: 10.1109/ICIEA.2017.8283126

Jinxin Cheng, Jiang Chen, Hang Xiang

引用次数: 0

Pedestrian detection based on multifractal analysis 基于多重分形分析的行人检测

2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA) Pub Date : 2017-06-18 DOI: 10.1109/ICIEA.2017.8282820

Baochang Zhang, Hainan Wang, Hong Zheng, Ya-wei Hou, Chenglong He, Baoguo Yu

引用次数: 1

High quality 3D reconstruction of indoor environments using RGB-D sensors 使用RGB-D传感器对室内环境进行高质量的3D重建

2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA) Pub Date : 2017-06-18 DOI: 10.1109/ICIEA.2017.8283120

Jun Wang, Shoudong Huang, Liang Zhao, J. Ge, S. He, Chengqi Zhang, Xiangyu Wang

{"title":"High quality 3D reconstruction of indoor environments using RGB-D sensors","authors":"Jun Wang, Shoudong Huang, Liang Zhao, J. Ge, S. He, Chengqi Zhang, Xiangyu Wang","doi":"10.1109/ICIEA.2017.8283120","DOIUrl":"https://doi.org/10.1109/ICIEA.2017.8283120","url":null,"abstract":"High-quality 3D reconstruction of large-scale indoor scene is the key to combine Simultaneous Localization And Mapping (SLAM) with other applications, such as building inspection and construction monitoring. However, the requirement of global consistency brings challenges to both localization and mapping. In particular, significant localization and mapping error can happen when standard SLAM techniques are used when dealing with the area of featureless walls and roofs. This paper proposed a novel framework aiming to reconstruct a high-quality, globally consistent 3D model for indoor environments using only a RGB-D sensor. We first introduce the sparse and dense feature constraints in the local bundle adjustment. Then, the planar constraints are incorporated in the global bundle adjustment. We fuse the point clouds in a truncated signed distance function volume, from which the high quality mesh can be extracted. Our framework leads to a comprehensive 3D scanning solution for indoor scene, enabling high-quality results and potential applications in building information system. The video of 3D models reconstructed by the method proposed in this paper is available at https://youtu.be/DWMP4YfeNeY.","PeriodicalId":443463,"journal":{"name":"2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132562838","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: 9

An overview of SiC MOSFET gate drivers SiC MOSFET栅极驱动器概述

2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA) Pub Date : 2017-06-18 DOI: 10.1109/ICIEA.2017.8282808

Qin Haihong, Ma Ceyu, Wang Dan, Xie Haotian, Zhu Ziyue, Xuan Kefeng, Wang Shi-shan

引用次数: 7

Predictive analytics for detecting sensor failure using autoregressive integrated moving average model 基于自回归积分移动平均模型的传感器故障预测分析

2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA) Pub Date : 2017-06-18 DOI: 10.1109/ICIEA.2017.8283153

K. Thiyagarajan, S. Kodagoda, Linh Van Nguyen

引用次数: 31

Energy-controlled optimization algorithm for rechargeable unmanned aerial vehicle network 可充电无人机网络能量控制优化算法

2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA) Pub Date : 2017-06-18 DOI: 10.1109/ICIEA.2017.8283046

Li Li, Jie Wu, Yixiang Xu, Jun Che, Jin Liang

引用次数: 6