Emerging trends in software development has been changed due to the huge amount of data, growth of internet, mobile, dynamic and smart applications. These applications consist of small, intelligent, flexible and distr...
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ISBN:
(纸本)9783642222023
Emerging trends in software development has been changed due to the huge amount of data, growth of internet, mobile, dynamic and smart applications. These applications consist of small, intelligent, flexible and distributed components known as agents. This research proposes agent-based autonomous controller (ABAC) architecture for managing road traffic. It uses time series of historical traffic intensity to estimate the appropriate time allocation for each signal at a given intersection. Our approach takes care of the exceptional appearance of rescue vehicles (e.g., ambulance) in order to ensure a smooth flow of the traffic. The ABAC architecture counts on several AI techniques germane to assessing the intensity of the traffic using image recognition algorithms. It also counts on environment sensors (sound sensors) in order to detect the advent of emergency vehicles. The ABAC traffic management architecture shows a high degree of adaptability leading to the least need for human intervention.
The proceedings contain 71 papers. The topics discussed include: practical and advanced image processing for security and recognition by thermal distributed image features;tropical wood species recognition system base...
ISBN:
(纸本)9781457714603
The proceedings contain 71 papers. The topics discussed include: practical and advanced image processing for security and recognition by thermal distributed image features;tropical wood species recognition system based on multi-feature extractors and classifiers;current technology on minimally invasive surgery and interventional techniques;networked control systems: time delays and robust control design issues;disturbance reduction on the small satellite actuator;integrated rate and inertial dependent Prandtl-Lshlinskii model for piezoelectric actuator;model reference adaptive control of cavity pressure in injection molding during filling and packing phases;fuzzy controller for beam stabilization in a heavy-ion synchrotron;an adaptive neuro fuzzy controller for cement kiln;wavelet denoising to analyze electroencephalogram signal of perfect pitch and non perfect pitch subjects;and compact computer vision for black tea quality evaluation based on the black tea particles.
The conventional microphone array near-field Fourier acoustic holography using Discrete Fourier Transform (DFT) is able to efficiently reconstruct sound field and acquire an image of noise distribution. However, Fouri...
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Geometric Object has various forms. Generally, Geometric Object is formed by several straight lines that the end point connects to the other end point of line, make certain angle, and make covered area. Therefore, to ...
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Among all the existing segmentation techniques, thresholding technique is one of the most popular one due to its simplicity, robustness and accuracy. Multi-thresholding is an important operation in many analyses which...
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Recent advances have shown that clothing appearance provides important features for person re-identification and retrieval in surveillance and multimedia data. However, the regions from which such features are extract...
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Today's retail stores are facing new challenges. While a few years ago competitive advantages could be achieved by well-stocked product portfolios and bargain prices both domains have been lost to internet shops. ...
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ISBN:
(纸本)9780980326741
Today's retail stores are facing new challenges. While a few years ago competitive advantages could be achieved by well-stocked product portfolios and bargain prices both domains have been lost to internet shops. To preserve and improve customer retention in stationary retail environments sophisticated customer approaches such as customized services or optimized retail environments are crucial. Therefore, comprehensive knowledge of the customers has to be available. In order to gain this knowledge without using vague customer surveys or short-time observations an automated solution is desirable. An approach for capturing and processing customer movement data by using network cameras and algorithms from the field of computer vision is introduced. Two image processing methods are presented and evaluated. The extracted information is used for analyzing and visualizing customer behavior by the popular regions algorithm and Markov chains. The approach is exemplarily applied to a testing environment showing considerable differences in customer behavior for two settings.
Accurate thresholding of skin cancer images is a very essential issue in medical diagnostic applications and biometric authentication and verification systems [1], another important issue in such applications relates ...
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Accurate thresholding of skin cancer images is a very essential issue in medical diagnostic applications and biometric authentication and verification systems [1], another important issue in such applications relates to its computational complexity. The objective of this study is to develop a more accurate and faster solution for estimating the optimal thresholding value of skin images. This work proposes a new algorithm for an Iterative Minimum Cross Entropy Thresholding method based on Log-normal distribution(MCET-Lognormal), under the assumption that the data of skin images is best modelled as a mixture of Log-normal distributions. The proposed method was applied on bi-modal skin cancer images and promising experimental results were obtained. Evaluation of the resulting segmented skin images shows that the proposed method yields better estimation of the optimal threshold than does the same MCET method with Gaussian distribution (MCET-Gaussian). It also reduces computational time compared to sequential search techniques.
In this paper, we present a method for video semantic mining. Speech signal, video caption text and video frame images are all key factors for a person to understand the video content. Through above observation, we br...
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In this paper, we present a method for video semantic mining. Speech signal, video caption text and video frame images are all key factors for a person to understand the video content. Through above observation, we bring forward a method which integrating continuous speech recognition, video caption text recognition and object recognition. The video is firstly segmented to a serial of shots by shot detection. Then the caption text and speech recognition results are treated as two paragraphs of text. The object recognition results are presented by bag of words. The above three aspects of texts are processed by part of speech and stemming. Then only the noun words are kept. At last a video is represented by three bags of words. The words are further depicted as a graph. The graph vertices stand for the words and the edges denote the semantic distance between two neighboring words. In the last step, we apply the dense sub graph finding method to mine the video semantic meaning. Experiments show that our video semantic mining method is efficient.
The proceedings contain 85 papers. The topics discussed include: ScaleLoc : a scalable real-time locating system for moving targets;research on advanced performance evaluation of video digital contents;high resolution...
ISBN:
(纸本)9783642241055
The proceedings contain 85 papers. The topics discussed include: ScaleLoc : a scalable real-time locating system for moving targets;research on advanced performance evaluation of video digital contents;high resolution image reconstructed by ARPS motion estimation and POCS;implementation of a real-time image object tracking system for PTZ cameras;statistical analyses of various error functions for pattern classifiers;FPGA implementation of image processing for real-time robot vision system;security requirements prioritization based on threat modeling and valuation graph;an efficient hardware countermeasure against differential power analysis attack;a study on smartphone APP authoring solution design for enhancing developer productivity;a study of disaster preparedness systems operations analysis and financial security measures of large banking network;and malware variant detection and classification using control flow graph.
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