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检索条件"主题词=Detection algorithms"

共 7380 条记录，以下是4971-4980 订阅

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An adaptive skin color detection algorithm with confusing backgrounds elimination

An adaptive skin color detection algorithm with confusing ba...

引用

IEEE International Conference on Image Processing

作者： Ming-Ji Zhang Wen Gao Graduate School of Chinese Academy of Sciences China Institute of Computing Technology Chinese Academy and Sciences China

In this paper a new skin detection method based on adaptive thresholds is proposed. Compared with the fixed threshold histogram method used widely, ours can find optimal thresholds to the different complex backgrounds. Four clues are summarized from the skin probability distribution histogram (SPDH) to help search candidates of optimum thresholds, and an ANN classifier is trained to select the final optimum threshold. A color deviation histogram (CDH) is also proposed to eliminate confusing backgrounds and refine optimal thresholds. The selection process of optimal thresholds is fast thus appropriate for real-time applications since no iterative operation is involved. Experimental results show that the proposed method can achieve better performance than the fixed threshold histogram method.

关键词： Skin detection algorithms Histograms Probability distribution Face detection Humans Pixel Adaptive filters Scanning probe microscopy Computers

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Precise change detection in multi-spectral remote sensing imagery using SIFT-based registration

Precise change detection in multi-spectral remote sensing im...

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International Conference on Multimedia Technology

作者： Mostafa Abdelrahman Asem Ali Aly A. Farag Computer Vision & Image Processing Laboratory (CVIP) University of Louisville Louisville KY USA

ISBN: (纸本)9781612847719

In this paper we propose a robust method for geometric co registration, and an accurate change detection technique based on statistical method for multi-temporal high-resolution satellite imagery. Lhe proposed algorithm is as the following: scale-invariant feature transform (SIFT) is used to extract a set of correspondence points in a pair, or multiple pairs, of images that are taken at different times and under different circumstances, then Random Sample Consensus (RANSAC) is used to remove the outlier set. the resulting inliers matched points is an accurate correspondences which used to register the given images, changes in registered images are identified using statistical analysis of image differences. Finally, Markov-Gibbs Random Field (MGRF) is used to model the spatial-contextual information contained in the resulting change mask. Experiments with generated synthetic multiband images, and LANDSAT5 Images, approved the accuracy the proposed algorithm.

关键词： Remote sensing Satellites Earth detection algorithms Feature extraction Statistical analysis Accuracy

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Time Dependent detection Analysis for a Virtual Radar Analysis Tool

Time Dependent Detection Analysis for a Virtual Radar Analys...

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International Radar Symposium

作者： Dimitri Tatarinov Una Karahasanovic Udo Schroder Oscar Gomez IEE S.A. 11 rue Edmond Reuter 5326 Contern LUXEMBOURG BMS Circuits 14 Place des vins de France 75012 Paris FRANCE

ISBN: (纸本)9781509043125

The probability of detection and the false alarm rate are the key parameters that define radar system performance. In order to obtain the best possible detection rate, while minimising false alarms, there is a need to measure and evaluate the performance of a system under development. In the case of vital signs monitoring systems, the target observation time is a very sensitive parameter. The two main unknowns are: when will the incident that we want to detect occur and how long must it be observed for a robust detection to be established. This paper shows a novel approach of so-called dynamic analysis of the detection probability for real or simulated data. This approach helps us to identify the statistical limits of the system and to find an optimum between the minimum observation time window and the maximum detection probability.

关键词： Tools Clutter Automobiles Radar detection Monitoring detection algorithms radar detection detection algorithms clutter Automobiles Cars false alarm probability limit system False alarms

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A high performance foreground detection algorithm for night scenes

A high performance foreground detection algorithm for night ...

引用

IEEE Workshop on Signal Processing Systems (SIPS)

作者： Tsung-Han Tsai Chih-Chi Huang Chen-Shuo Fan Dept. of Electrical Engineering National Central University Taoyuan Taiwan

Foreground detection is designed to separate the objects from a background scene. However, night scenes always contain high dynamic illumination variety so that the performance on detection drops largely. In this paper, we present a new foreground detection algorithm which is applicable to scenes with complicated illumination and shadow. This new algorithm utilizes multiple regions to perform background classification. Consequently human vision can focus on moving objects and the interferences such as night illumination or shadow can be effectively eliminated. Because this algorithm can eliminate most interference, therefore moving objects can be segmented more precisely. As our experiment, the precision of nigh scene foreground detection is highly improved compared with other techniques.

关键词： Lighting Classification algorithms Adaptation models Image segmentation detection algorithms Interference Convergence

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A heuristic approach to optimization of the decision-directed maximum-likelihood feedforward carrier phase error detection algorithm

A heuristic approach to optimization of the decision-directe...

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IEEE Symposium on Computers and Communications (ISCC)

作者： R. Danesfahani T. Jeans Faculty of Engineering University of Kashan Kashan Iran School of Electronics Computing and Mathematics University of Surrey Guildford Surrey UK

Using a heuristic approach, the performance of the self-synchronized decision-directed maximum-likelihood (ML) feedforward (FF) carrier phase error detection (PED) algorithm has been optimized. Compared to the original algorithm, it has been shown that for uncoded single channel (O)QPSK modems the optimized algorithm has a better phase error variance at low to medium signal to noise ratio (SNR). Further simulations have shown that the noise performance of the optimized algorithm at medium to high SNRs is superior to that of some well-known algorithms; the noise performance approaches the Cramer-Rao bound (CRB). This proves that the optimized algorithm has less tracking jitter at medium to high SNR which is a desirable feature in improving the BER performance.

关键词： Maximum likelihood detection detection algorithms Filters Phase detection Signal to noise ratio Data mining Maximum likelihood estimation Modems Error correction Phase estimation

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Fire detection System with YOLO and Flicker Analysis Using HSV Color Space Masking

Fire Detection System with YOLO and Flicker Analysis Using H...

引用

International Conference on ICT For Smart Society (ICISS)

作者： Calvin Figo Agil Alunjati Ulva Elviani Fadhil Hidayat School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia

ISBN: (数字)9798350389654

ISBN: (纸本)9798350389661

Early and reliable fire detection is crucial for minimizing fire damage and supporting firefighting efforts. Traditional sensor-based fire detection systems have limitations, prompting exploration into video analytics using computer vision techniques. This paper addresses the increasing fire incidents in Jakarta, Indonesia, underscoring the need for improved detection methods. We propose a video analytics-based fire detection system utilizing object detection with YOLO and flickering analysis with HSV color space. This approach aims to reduce false alarms by combining fire characteristics like flickering and color analysis, ultimately enhancing detection accuracy and contributing to improved fire safety measures. The proposed system achieved a 71.5% accuracy rate with 28.42 % fault detection rate, demonstrating proficiency in recognizing and differentiating real fire with static-fire objects, in order to reduce false alarms. Future development will focus on refining the fire detection algorithm to better capture the characteristics of moving fires and improving fire classification to reduce false positives, addressing the challenge of distinguishing real fires from highly realistic fire videos.

关键词： YOLO Accuracy Fluctuations Image color analysis Heuristic algorithms Fault detection Visual analytics Refining detection algorithms Fire safety

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Real-Time Robust Pinch detection Algorithm for Automobile Applications

Real-Time Robust Pinch Detection Algorithm for Automobile Ap...

引用

International Conference on Intelligent Transportation

作者： Won-Sang Ra Hye-Jin Lee Tae-Sung Yoon Jin-Bae Park Department of Electrical and Electronic Engineering Yonsei University Seoul South Korea Department of Electrical Engineering Changwon NatE28099l University Kyongnam South Korea

A robust pinch detection algorithm which can be implemented in a cheap microprocessor is proposed for safety power window systems. To deal with the problems caused by performance degradation of a Hall sensor or real driving situations, the proposed algorithm makes use of the H infin state estimation technique. The motivation of this approach comes from the advantage that the H infin filter can minimize or bound the worst-case estimation error energy for all bounded energy disturbances. Herein, the pinch torque rate estimator is derived by applying the steady-state H infin filter to the augmented model which includes the motor dynamics and an additional torque rate state. Then, by redesigning the estimator to be appropriate for real-time implementation, the torque rate estimate can be calculated more simply than the previous method (Lee et al., 2005). Experimental results verify that, with a small amount of computation, the proposed pinch detection algorithm provides fast pinch detection performance similar to the existing method. Furthermore, it guarantees robustness against the worst-case measurement noises

关键词： Robustness detection algorithms Automobiles Torque State estimation Filters Microprocessors Safety Degradation Estimation error

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A support vector machine based algorithm for jamming attacks detection in cellular networks

A support vector machine based algorithm for jamming attacks...

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Conference on Wireless Advanced (WiAD)

作者： Javad Afshar Jahanshahi Seyed Ali Ghorashi Mohammad Eslami Cognitive Telecommunications Research Group Department of Electrical Engineering Shahid Beheshti University Tehran Iran

In this paper, a support vector machine algorithm is proposed for jamming detection at the base station in cellular networks. The proposed jamming detection process uses only inherent information which is available in common receivers and does not need excessive hardware requirements for external information. Support vector machine algorithm is used in jamming detection process to improve the performance of the jamming detection algorithm and to reduce the required hardware complexity. The performance of the proposed algorithm is modeled in a TETRA network and simulation results show acceptable results in a wide range of user terminal velocities with comparison to other conventional methods.

关键词： Jamming Support vector machines detection algorithms Receivers Classification algorithms Base stations Synchronization

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A Lightweight Traffic Sign detection Algorithm Based on YOLOv5s

A Lightweight Traffic Sign Detection Algorithm Based on YOLO...

引用

Robotics, Artificial Intelligence and Intelligent Control (RAIIC), International Conference on

作者： Jiahao Sun Jifeng Liang Zhengda Liu School of Electronics and Information Engineering Wuxi University Wuxi Jiangsu China

ISBN: (数字)9798350352627

ISBN: (纸本)9798350352634

In the context of the rapidly developing autonomous driving technology, developing efficient and accurate traffic sign detection algorithms is of great significance. This paper proposes a lightweight algorithm based on YOLOv5s, aimed at enhancing detection performance and achieving parameter lightweighting. Firstly, by employing Ghost convolutions and Depthwise Convolutions (DW Conv) to construct a new backbone module, it successfully reduces the number of parameters and computational cost, thus improving the efficiency of the algorithm. Secondly, the introduction of the SPDC module enhances the algorithm’s capability of extracting information from multi-scale features, further improving the model’s detection accuracy. In addition, incorporating the CARAFE upsampling operator helps enhance the spatial resolution of the feature network, allowing the model to more accurately restore the details of the targets. The study focused on categories in the TT100K dataset with more than 200 instances shows that the improved model surpasses comparative methods in terms of average precision, overall performance, parameter quantity, and model size. This lightweight algorithm not only effectively enhances the accuracy of traffic sign detection but is also easy to deploy on embedded devices for real-time online detection, further advancing the intelligent level of environmental perception in autonomous driving.

关键词： YOLO Performance evaluation Accuracy Computational modeling Feature extraction Spatial resolution detection algorithms

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Energy-aware objects abandon / removal detection

Energy-aware objects abandon / removal detection

引用

IEEE Conference on Advanced Video and Signal Based Surveillance (AVSS)

作者： Alessandro Lanza Michele Magno Davide Brunelli Luigi Di Stefano Luca Benini DEIS University of Bologna Bologna Italy

A major issue for video surveillance embedded systems is the need to continuously perform a number of highly demanding operations even when the analyzed scene does not show peculiar or interesting features, so that power consumption is a critical issue. In this paper we present a low-power multimodal embedded video surveillance system aimed at detecting objects abandoned/removed in/from a static monitored scene. Energy-awareness is achieved by means of an efficient and scalable objects abandon/removal detection algorithm, a Linux governor that controls CPU frequency and operating mode so as to establish an optimal trade-off between fulfilling the application efficiency-accuracy requirements and maximizing battery life and, finally, a pyroelectric infrared sensor that allows to wake up the CPU only when video processing is actually needed.

关键词： Hardware detection algorithms Accuracy Video surveillance Cameras Linux

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