2005 IEEE International Conference on Information Acquisition最新文献_第4页

Force sensor based motion control of wheeled mobile robots 基于力传感器的轮式移动机器人运动控制

2005 IEEE International Conference on Information Acquisition Pub Date : 1900-01-01 DOI: 10.1109/ICIA.2005.1635146

H. Su, M. Liu

引用次数: 1

Development of a nonlinear PID controller with saturated function design 开发一种具有饱和函数的非线性PID控制器

2005 IEEE International Conference on Information Acquisition Pub Date : 1900-01-01 DOI: 10.1109/ICIA.2005.1635134

Xiaoyin Shao, Dong Sun, Yuxin Su

引用次数: 4

Microwave-based sensor for detection of a shortage in tobacco box 基于微波的烟盒缺货检测传感器

2005 IEEE International Conference on Information Acquisition Pub Date : 1900-01-01 DOI: 10.1109/ICIA.2005.1635123

Weilian Wang, Ming Huang, Zhengrao Bai, Liting Yao

引用次数: 4

Face recognition based on wavelet transform and SVM 基于小波变换和支持向量机的人脸识别

2005 IEEE International Conference on Information Acquisition Pub Date : 1900-01-01 DOI: 10.1109/ICIA.2005.1635115

Bing Luo, Yun Zhang, Yunhong Pan

引用次数: 26

Dynamic sensing of human eye using a high speed camera 利用高速摄像机实现人眼动态感知

2005 IEEE International Conference on Information Acquisition Pub Date : 1900-01-01 DOI: 10.1109/ICIA.2005.1635109

Y. Kurita, Y. Iida, R. Kempf, M. Kaneko, H. Mishima, H. Tsukamoto, E. Sugimoto

引用次数: 15

RLS-based blind adaptive beamforming algorithm for antenna array in CDMA systems 基于rls的CDMA系统天线阵盲自适应波束形成算法

2005 IEEE International Conference on Information Acquisition Pub Date : 1900-01-01 DOI: 10.1109/ICIA.2005.1635100

Jian Yang, H. Xi, Feng Yang

引用次数: 6

Computer vision based real-time information acquisition for transport traffic 基于计算机视觉的交通信息实时采集

2005 IEEE International Conference on Information Acquisition Pub Date : 1900-01-01 DOI: 10.1109/ICIA.2005.1635075

Kim-Sung Jie, Ming Liu

引用次数: 9

Matching feature points and discarding false matching pairs 匹配特征点，丢弃错误的匹配对

2005 IEEE International Conference on Information Acquisition Pub Date : 1900-01-01 DOI: 10.1109/ICIA.2005.1635132

Y. Wu, M. Dai

引用次数: 3

Mono-, multi-layer nanostructured porous films and gas sensors 单层、多层纳米结构多孔膜和气体传感器

2005 IEEE International Conference on Information Acquisition Pub Date : 1900-01-01 DOI: 10.1109/ICIA.2005.1635087

F. Sun, W. Cai, Yuenkei Li, L. Jia, Fang Lu

{"title":"Mono-, multi-layer nanostructured porous films and gas sensors","authors":"F. Sun, W. Cai, Yuenkei Li, L. Jia, Fang Lu","doi":"10.1109/ICIA.2005.1635087","DOIUrl":"https://doi.org/10.1109/ICIA.2005.1635087","url":null,"abstract":"A simple and flexible strategy is presented for synthesis of mono or multi-layer nanostructured ordered porous films on any desired substrates with flat or even curved surface, based on the fact that polystyrene sphere colloidal monolayer on glass substrate can lift off and floated on some precursor solutions, which can, in turn, be transferred onto any substrates by picking it up. SnO/sub 2/ ordered nanostructured porous films are thus successfully synthesized on the cylindrical surface, the concave surface and the spherical surface, respectively, just by taking the easily acquired SnCl/sub 4/ solution as precursor. More importantly, the mono and multi-layer porous films are also directly synthesized on commercially supplied ceramic or porcelain tubes which are used for the substrate of gas sensors. And hence, the SnO2 ordered nanostructured porous gas-sensor is constructed. Sensitivity of the sensor can be easily controlled by changing the sizes of polystyrene spheres. Such method is universal and suitable for synthesis of many other oxides or doped porous films, mesoporous/macroporous gas sensor films and even the hetero-multi-layer porous films on the curved surfaces just by changing the compositions of the precursors or alternatively repeating this strategy. This strategy provides a good way to construct nanostructured gas-sensors and practical possibility of the nanostructured devices in the near future.","PeriodicalId":136611,"journal":{"name":"2005 IEEE International Conference on Information Acquisition","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124003026","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

Face detection by color and multilayer feedforward neural network 基于颜色和多层前馈神经网络的人脸检测

2005 IEEE International Conference on Information Acquisition Pub Date : 1900-01-01 DOI: 10.1109/ICIA.2005.1635143

Chiunhsiun Lin

{"title":"Face detection by color and multilayer feedforward neural network","authors":"Chiunhsiun Lin","doi":"10.1109/ICIA.2005.1635143","DOIUrl":"https://doi.org/10.1109/ICIA.2005.1635143","url":null,"abstract":"In this paper, we introduce a novel approach for automatic detection of human faces embedded in dissimilar lighting. The proposed system consists of two primary parts. The first part is to convert the input RGB color images to a binary image directly using color segmentation. Because the absolute values of r, g, and b are totally different with the various skin colors in the altered lighting conditions and the relative value between r, g, and b are almost similar with the different skin colors in changed brightness circumstances, we use the relative value between r, g, and b in the color segmentation process to binarize the RGB color images directly instead of \"color images to gray level images, then binary ones\". For this reason, our system is very robust for different lighting conditions. The second part of the proposed system is to search the potential face regions and perform the task of face detection. In the second part, each face candidate is obtained from the isosceles-triangle criterion that is based on the rules of \"the combination of two eyes and one mouth\", and then to be normalized to a standard size (60*60 pixels). Next, each of these normalized potential face regions are fed to neural networks function to obtain the location of the face region. The proposed face detection system can detect color multiple faces embedded in dissimilar lighting conditions. Moreover, it can conquer different size, varying pose and expression. Experimental results demonstrate that an approximately 97% success rate is achieved and the relative false estimation rate is very low.","PeriodicalId":136611,"journal":{"name":"2005 IEEE International Conference on Information Acquisition","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127978133","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: 17