中国科学院机构知识库网格系统: 检索

Psychological Stress Level Detection Based on Heartbeat Mode 期刊论文 OAI收割
APPLIED SCIENCES-BASEL, 2022, 卷号: 12
作者: Hu, Dun; Gao, Lifu

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autonomic nervous system heartbeat mode heart rate variability k-nearest neighbors stress recognition

Sequential Combination of Femtosecond Laser Ablation and Induced Micro/Nano Structures for Marking Units with High-Recognition-Rate 期刊论文 OAI收割
ADVANCED ENGINEERING MATERIALS, 2019, 卷号: 21, 期号: 8
作者: Sun, Xiaoyun; Wang, Wenjun; Mei, Xuesong; Pan, Aifei; Zhang, Ju

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收藏 | 浏览/下载：60/0 | 提交时间：2019/09/24

combined markings femtosecond laser ablation induced micro nano structures recognition rate

Research on infrared dim-point target detection and tracking under sea-sky-line complex background (EI CONFERENCE) 会议论文 OAI收割
International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications, May 24, 2011 - May 24, 2011, Beijing, China
作者: Dong Y.-X.; Zhang H.-B.; Li Y.; Li Y.; Li Y.

收藏 | 浏览/下载：109/0 | 提交时间：2013/03/25

Target detection and tracking technology in infrared image is an important part of modern military defense system. Infrared dim-point targets detection and recognition under complex background is a difficulty and important strategic value and challenging research topic. The main objects that carrier-borne infrared vigilance system detected are sea-skimming aircrafts and missiles. Due to the characteristics of wide field of view of vigilance system the target is usually under the sea clutter. Detection and recognition of the target will be taken great difficulties.There are some traditional point target detection algorithms such as adaptive background prediction detecting method. When background has dispersion-decreasing structure the traditional target detection algorithms would be more useful. But when the background has large gray gradient such as sea-sky-line sea waves etc.The bigger false-alarm rate will be taken in these local area.It could not obtain satisfactory results. Because dim-point target itself does not have obvious geometry or texture feature in our opinion from the perspective of mathematics the detection of dim-point targets in image is about singular function analysis.And from the perspective image processing analysis the judgment of isolated singularity in the image is key problem. The foregoing points for dim-point targets detection its essence is a separation of target and background of different singularity characteristics.The image from infrared sensor usually accompanied by different kinds of noise. These external noises could be caused by the complicated background or from the sensor itself. The noise might affect target detection and tracking. Therefore the purpose of the image preprocessing is to reduce the effects from noise also to raise the SNR of image and to increase the contrast of target and background. According to the low sea-skimming infrared flying small target characteristics the median filter is used to eliminate noise improve signal-to-noise ratio then the multi-point multi-storey vertical Sobel algorithm will be used to detect the sea-sky-line so that we can segment sea and sky in the image. Finally using centroid tracking method to capture and trace target. This method has been successfully used to trace target under the sea-sky complex background. 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).

A new method of target recognition based on rough set and support vector machine (EI CONFERENCE) 会议论文 OAI收割
2nd International Conference on Image Analysis and Signal Processing, IASP'2010, April 12, 2010 - April 14, 2010, Xiamen, China
作者: He X.

收藏 | 浏览/下载：18/0 | 提交时间：2013/03/25

Automatic target recognition (ATR) is an important task in image application. This paper concentrates on two key subroutines of ATR system: Pre-treatment and design of classifier. In the pre-treatment subroutine a new method based on Rough Set (RS) is proposed to partition the original sample set into some subsets and calculate their class membership so that some samples can be chosen by class membership to be trained. After pre-treatment an iterative algorithm based on Rough Set and Support Vector Machines (IRSSVM) is introduced to design a classifier for recognizing two types of targets. The experiment results show that IRSSVM needs less training time and the classifier is simpler and has more generalization and higher recognition rate. 2010 IEEE.

Using bidirectional binary particle swarm optimization for feature selection in feature-level fusion recognition system (EI CONFERENCE) 会议论文 OAI收割
2009 4th IEEE Conference on Industrial Electronics and Applications, ICIEA 2009, May 25, 2009 - May 27, 2009, Xi'an, China
作者: Wang D.; Wang Y.; Wang Y.; Wang Y.; Wang Y.

收藏 | 浏览/下载：21/0 | 提交时间：2013/03/25

In feature-level fusion recognition system the other is optimizing system sensor design to get outstanding cost performance. So feature selection become usually necessary to reduce dimensionality of the combination of multi-sensor features and improve system performance in system design. In general there are two main missions. One is improving the recognition correct rate as soon as possible the optimization is usually applied to feature selection because of its computational feasibility and validity. For further improving recognition accuracy and reducing selected feature dimensions this paper presents a more rational and accurate optimization Bidirectional Binary Particle Swarm Optimization (BBPSO) algorithm for feature selection in feature-level fusion target recognition system. In addition we introduce a new evaluating function as criterion function in BBPSO feature selection method. At the last we utilized Leave-One-Out method to validate the proposed method. The experiment results show that the proposed algorithm improves classification accuracy by two percentage points while the selected feature dimensions are less one dimension than original Particle Swarm Optimization approach with 16 original feature dimensions. 2009 IEEE.

A method of aircraft image target recognition based on modified PCA features and SVM (EI CONFERENCE) 会议论文 OAI收割
9th International Conference on Electronic Measurement and Instruments, ICEMI 2009, August 16, 2009 - August 19, 2009, Beijing, China
Donghe W.; Xin H.; Wei Z.; Huilong Y.

收藏 | 浏览/下载：28/0 | 提交时间：2013/03/25

Automatic target recognition(ATR) is an important task in image application. This paper concentrates on two key subroutines of ATR system: Dimensionality reduction and Classifier. After pretreatment on original features a self-organizing neural network trained with the Hebbian rule is used to extract the principal component features. Then a classifier based on Directed Acyclic Graph Support Vector Machines(DAGSVM) is adopted to recognize more than two types of aircraft targets. The experiment results show the proposed method achieves better subset features and higher recognition rate. 2009 IEEE.

Non-contact and on-line cone diameter measuring based on high speed linear CCD (EI CONFERENCE) 会议论文 OAI收割
2nd International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optical Test and Measurement Technology and Equipment, November 2, 2005 - November 5, 2005, Zian, China
Guohui Z.; Jianhua W.

收藏 | 浏览/下载：34/0 | 提交时间：2013/03/25

The remarkable improvement of sensing and processing hardware performance makes the non-contact on-line high accuracy and high speed measuring possible by means of linear CCD. The goal of this pager is to describe the key questions on designing the cone diameter detecting system by linear CCD. This paper first describes the detecting scheme. In particular the factors affecting accuracy such as resolution voltage difference between neighbor pixels detecting rate and so on are analyzed and the quantitative estimation equations are provided. CCD takes on the photoelectric translation and measuring component double functions so the waveform of CCD output signal and the affecting factors merit deep discussion. On the basis of discussion several principles that can be used to improve the boundary recognition accuracy are presented.

The signal extraction of fetal heart rate based on wavelet transform and BP neural network (EI CONFERENCE) 会议论文 OAI收割
Third International Conference on Experimental Mechanics and Third Conference of the Asian Committee on Experimental Mechanics, November 29, 2004 - December 1, 2004, Singapore, Singapore
Hong Y. X.; Cheng Z. B.; Dai F. H.

收藏 | 浏览/下载：25/0 | 提交时间：2013/03/25

This paper briefly introduces the collection and recognition of bio-medical signals the other threading is analyzing data. Using the method designs the method to collect FM signals. A detailed discussion on the system hardware it is broaden to analyze the signal in real-time. Wavelet transform to remove the main interference in the FM and by adding time-window to recognize with BP network structure and functions is also given. Under LabWindows/CVI Finally the results of collecting signals and BP networks are discussed.8 pregnant women's signals of FM were collected successfully by using the sensor. The correctness rate of BP network recognition is about 83.3% by using the above measure. the hardware and the driver do compatible the hardware equipment work properly actively. The paper adopts multi threading technology for real-time analysis and makes use of latency time of CPU effectively expedites program reflect speed improves the program to perform efficiency. One threading is collecting data

自动指纹识别算法的识别性能研究 学位论文 OAI收割
工学博士, 中国科学院自动化研究所: 中国科学院研究生院, 2003
作者: 任群

收藏 | 浏览/下载：62/0 | 提交时间：2015/09/02

模式识别指纹特征统计分析类Bootstrap估计错误率性能评估 Pattern Recognition Fingerprint Features Statistical Analysis Subset Bootstrap Method Error Rate Performace Evaluation

An improved BP algorithm for pattern recognition 会议论文 OAI收割
4th international conference on signal processing (icsp 98), beijing, peoples r china, oct 12-16, 1998
Zeng YJ; Wang XD; Wang SJ

收藏 | 浏览/下载：23/0 | 提交时间：2010/10/29

BP algorithm pattern recognition neural network misclassification rate