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检索条件"主题词=Adaboost algorithm"

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A visual tracking system using an RFID tag

A visual tracking system using an RFID tag

引用

Conference on Internet Imaging VI

作者： Hontani, H Yamagata Univ Yonezawa Yamagata 992 Japan

ISBN: (纸本)0819456438

We propose a visual tracking system that uses RFID-tags to identify objects. The system firstly identifies an object in front of the camera, and pulls up data of the object from the database. The data includes a cad model of the object that is used for estimating 3D motion relative to the camera and a set of image features that is used for detecting the object in the initial image. The set of image features is generated based on the cad model by means of the adaboost algorithm and distinguishes the object in images from the backgrounds efficiently. Identifying the object, the system processes images using models that are specialized in the object in front of the camera.

关键词： RFID-tag visual tracking haar-like feature adaboost algorithm

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News Topic-typed Microblog Opinion Sentence Recognition 2

News Topic-typed Microblog Opinion Sentence Recognition

引用

2nd IEEE International Conference on Computer and Communications (ICCC)

作者： Fang, Yi Cheng Du, Ya Jun Tang, Ming Wei Xihua Univ Sch Comp & Software Engn Chengdu Sichuan Peoples R China

ISBN: (纸本)9781467390262

In recent years, with the development of the micro-blog platform, text mining technology in microblog is also developing fastly. Microblog's opinion sentence recognition task is the prerequisite of emotional polarity classification and public opinion analysis. Because of news topic-typed microblog's colloquial feature and the freedom of language structure, we put forward a combination classification method to identify the opinion sentence in microblog. Based on rules and adaboost, we use three filter rules and news topic-typed microblog's text features as weak classifiers of adaboost algorithm. Comparing with the traditional dictionary method and SVM method, the experimental results show that the method of this paper has achieved a good performance in the task of identifying the news topic-typed micro-blog's opinion sentence.

关键词： microblog oplnton mining natural language processing adaboost algorithm

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Passenger Detection for Subway Transportation Based on Video 10

Passenger Detection for Subway Transportation Based on Video

引用

10th International Conference on Natural Computation (ICNC)

作者： Chen, Yingjie Zhang, Liquan Wang, Jia Beijing Univ Civil Engn & Architecture Dept Elect & Engn Beijing Peoples R China

ISBN: (纸本)9781479951512

The purpose of this paper is to analyze passengers' moving direction through the video shot in the entrances and exits of the subway stations. The results of the analysis will be helpful to relevant departments to manage the traffic condition, making a decision in the face of emergency. First of all, this paper adopts Haar features and adaboost algorithm to implement the detection of human's head through OpenCV;Secondly, this paper uses color histogram in the head recognition and an improved algorithm that adds the step of comparing the pixel value of the location coordinates in consecutive frames is proposed;At last, the paper realizes the human tracking through the establishment of target tracking chain and puts forward to analyze passengers' moving direction through space coordinate information.

关键词： adaboost algorithm head detection color histogram target tracking

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A Real-Time Vision-Based Framework for Human-Robot Interaction

引用

2nd International Visual Informatics Conference

作者： Lam, Meng Chun Prabuwono, Anton Satria Arshad, Haslina Chan, Chee Seng Univ Kebangsaan Malaysia Fac Informat Sci & Technol Ukm Bangi 43600 Selangor De Malaysia Univ Malaya Fac Comp Sci & Informat Technol Kuala Lumpur 530603 Malaysia

ISBN: (纸本)9783642251900;9783642251917

Building human-friendly robots which are able to interact and cooperate with humans has been an active research field in recent years. A major challenge in this field is to develop robots that can interact and cooperate with humans by understanding human communication modalities. Nonetheless, human face is a dynamic object and has a high degree of variability in its appearance, which makes face detection a difficult problem. In this paper, we present a real-time vision-based framework to detect human face and analysis of the human face direction in window area to interact with robot. A cascade of feature detectors trained with boosting technique has been employed. Experimental results using servo motors connect to SD21 and PIC16F887A microcontroller: and the MIABOT Pro have validated our approach. Our future work is to build an intelligent wheelchair whose motion can be controlled by the user's face direction.

关键词： Vision-based framework human-robot interaction face detection adaboost algorithm Visual Informatics

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Fast Vision-based Pedestrian Traffic Light Detection 1

Fast Vision-based Pedestrian Traffic Light Detection

引用

1st IEEE Conference on Multimedia Information Processing and Retrieval (MIPR)

作者： Wu, Xue-Hua Hu, Renjie Bao, Yu-Qing Southeast Univ Sch Elect Engn Nanjing Jiangsu Peoples R China Nanjing Normal Univ NARI Sch Elect Engn & Automat Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781538618578

Detection of pedestrian traffic light is very important for the visually impaired. However, fast but accurate vision-based detection is not an easy task due to the complexity of background and illumination. In this paper, a fast vision-based detection system is designed. In the designed system, the background filter is applied to identify the candidate regions of pedestrian traffic lights. And the cascade classifier obtained by the adaboost algorithm based on the multi-layer features is used to detect the pedestrian traffic lights. Testing results verifies the effectiveness of the designed system.

关键词： fast pedestrian traffic light detection adaboost algorithm the multi-layer features

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Using Boosted k-Nearest Neighbour algorithm for Numerical Forecasting of Dangerous Convective Phenomena 19th

Using Boosted k-Nearest Neighbour Algorithm for Numerical Fo...

引用

19th International Conference on Computational Science and Its Applications (ICCSA)

作者： Stankova, E. N. Khvatkov, E., V St Petersburg State Univ 7-9 Univ Skaya Nab St Petersburg 199034 Russia

ISBN: (纸本)9783030243050

The authors propose a boosted k-nearest neighbour algorithm for numerical forecasting of dangerous convective phenomena. The algorithm is applied for processing the output data of the numerical cloud model. The results show that boosted algorithm is able to predict the very fact of convective phenomena occurrence with the high accuracy, but it is not so good in distinguishing the specific type of convective phenomena. Comparison with the k-NN algorithm without boosting shows that boosting resulted in better accuracy of forecasting.

关键词： Machine learning Naive bayes classifier Boosted k-nearest neighbour algorithm adaboost algorithm Support-vector machine model Numerical model of convective cloud Weather forecasting Thunderstorm forecasting

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AN INTELLIGENT VIRTUAL FENCE SECURITY SYSTEM FOR THE DETECTION OF PEOPLE INVADING

AN INTELLIGENT VIRTUAL FENCE SECURITY SYSTEM FOR THE DETECTI...

引用

IEEE 9th International Conference on Ubiquitous Intelligence and Computing (UIC) / IEEE 9th International Conference on Autonomic and Trusted Computing (ATC)

作者： Chen, Jun-Horng Tseng, Teng-Hui Lai, Chin-Lun Hsieh, Sheng-Ta Oriental Inst Technol Dept Commun Engn New Taipei City Taiwan

ISBN: (纸本)9780769548432;9781467330848

This work proposes an intelligent and interactive virtual fence system for security management in a danger- or accident-prone area. The proposed system is designed to be realized in an outdoor and wide-area park. With the proposed system, users can visually and arbitrarily define the polygonic alert area for the sake of security. The Gaussian Mixture Model (GMM) and adaboost algorithms are modified and integrated in this work to provide a robust human detection. As soon as the invading people is detected and located in the interior of the alert area, the proposed system will immediately alarm the security guards by MMS of cellular networks or a customized App installed in smart phones. Besides, this work also proposes a sliding-window based alarm mechanism to practically and robustly improve the detection rate and reduce the false alarm rate of detection. The experimental results will demonstrate that the proposed system can be indeed applied in a real field and provide a satisfied performance.

关键词： Virtual Fence Gaussian Mixture Model Pedestrian Detection adaboost algorithm

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A Strong Classifier Model Oriented to the Financial Risk Warning of Listed Company 6

A Strong Classifier Model Oriented to the Financial Risk War...

引用

6th International Conference on Intelligent Systems Design and Engineering Applications (ISDEA)

作者： Shuo, Yu Liaoning Jianzhu Vocat Univ Liaoyang 111000 Peoples R China

ISBN: (纸本)9781467393935

A strong classifier model oriented to the financial risk warning of listed company has played an important role in the risk analysis of enterprise finance. Based on the BP_adaboost composed of BP neural network and adaboost algorithm, a strong classifier model of enterprise finance is designed and established, and is verified with the actual data. In the first, the evaluation index has the largest correlation to the warning result of enterprise finance has been filtered through the significance analysis and factor analysis of typical data. After that, the data item corresponding to the evaluation index is taken into the strong BP_adaboost classifier model, in order to compute the classification results. Finally, the classification result of the weak BP classifier is computed and compared with the one of the strong BP_adaboost classifier model. The experimental results show that the accuracy of strong BP_adaboost classifier is higher than the one of weak BP classifier, and the strong BP_adaboost classifier has better stability and higher reliability.

关键词： Financial Risk Warning Strong Classifier Model BP Neural Network adaboost algorithm Classification Accuracy Stability

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Fast Face Detection Based on Skin Color Segmentation Using Single Chrominance Cr 7

Fast Face Detection Based on Skin Color Segmentation Using S...

引用

7th International Congress on Image and Signal Processing (CISP)

作者： Hu, Xiao Peng, Shaohu Yan, Jiyong Zhang, Na Guangzhou Univ Sch Mech & Elect Engn Guangzhou 510006 Guangdong Peoples R China Guangzhou Panyu Polytech Jewelry Inst Guangzhou 510006 Guangdong Peoples R China

ISBN: (纸本)9781479958351

In this paper, a simple and fast algorithm was proposed to detect face. Firstly, some interest points marking skin regions were searched by only using simple chrominance Cr information instead of simultaneously using chrominance Cr and Cb. And then, a conventional and popular adaboost algorithm was employed to make a decision whether around the detected interest points was there face and then located the face if there was. 400 face patches were translated into YCbCr space, and it was found from the 400 face patches that skin Cr histogram overlapped a little with non-skin Cr histogram and its cut-off was about 137. From LFW database, another 215 facial images of 108 subjects were random selected to test the proposed method. Compared with other interest detection methods, the detection based simple Cr method can not only find out all face regions, but also the number of its detected interest points was the least and the whole detection time was the least too. Therefore, the proposed method was an effective face detection method.

关键词： YCbCr space Interest points adaboost algorithm Cr distribution

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Development of Machine Learning Based State-of-Charge Prediction Model for Plug-in Electric Vehicle's Relocation in Sharing System

Development of Machine Learning Based State-of-Charge Predic...

引用

13th International Symposium on Linear Drives for Industry Applications (LDIA)

作者： Deb, Subhasish Goswami, Arup Kumar Hajra, Bikram Ghosh Chetri, Rahul Lamichane Roy, Mitadru Roy, Rajesh Mizoram Univ Aizawl 796004 India Natl Inst Technol Silchar Silchar 788010 India

This paper presents a Plug-in electric vehicle (PEV) relocation strategy in a sharing system considering machine learning based state-of-charge (SOC) prediction model. The proposed work involves the machine learning approaches like the adaboost algorithm and XGBoost algorithm for PEVs SOC prediction in relocation problems for the first time. Also, the low-capacity batteries of PEVs are considered as it is affordable by the common people with less charging time. It is also believed that the large number of low capacities PEVs based taxi owners in metropolitan cities will be attracted towards relocation-based sharing system considering machine learning based SOC prediction model. The customer request for sharing PEVs will be reflected in the management system at the beginning. Assuming all the PEVs with a certain level of SOC during pre-relocation are connected to the management system. The customer request for PEVs service will be assigned to the nearest PEVs depending on the predicted value of SOC by machine learning approaches. The machine learning-based predicted value of PEVs SOC will help the management system to identify the nearest PEVs for the customer sharing system. The present work steps are listed here. Firstly, the PEVs with higher predicted SOC value by machine learning have been shared with the customer from the nearest location considering descending order of their SOC. Further, the rest of the PEVs will be assigned to the nearest charging station by the PEV sharing management system. Secondly, the customer request is assigned from the station to relocate PEVs with higher SOC values in descending order. Different case studies are assumed including one practical scenario of Mumbai, India. The optimization problem of multi-depot vehicle routing problem (MDVRP) with the minimization of relocation cost has been solved by IBM CPLEX optimizer in this work. Finally, the proposed work efficacy has been demonstrated with some validated results including less r

关键词： adaboost algorithm and XGBoost algorithm machine learning approaches plug-in electric vehicle (PEV) relocation in sharing system state-of-charge (SOC)

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