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Research on Radar Echo signal Noise processing and Adaptive RLS Noise Reduction Algorithm 12

Research on Radar Echo Signal Noise Processing and Adaptive ...

引用

12th International symposium on computational intelligence and Design (ISCID)

作者： Luo, Jingxin Wen, Hui Univ Elect Sci & Technol China Res Inst Elect Sci & Technol Chengdu Peoples R China

ISBN: (纸本)9781728146522

In the process of signal processing, noise will affect the accuracy of data processing and research. The accuracy obtained by different algorithms is different[1]. In this paper, a variety of radar signal denoising algorithms are discussed and simulated. Finally, the self-adaptive noise processing method[2] is described and optimized. The self-adaptive noise cancellation method is obtained. The comparison between the simulated data and the actual measurement data is obtained. It is proved that the self-adaptive RLS noise reduction effect studied in this paper is better, thus reducing the influence of noise.

关键词： signal processing noise noise reduction self-adaptive RLS

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Safe Human-Computer Interface Based On Efficient image processing Algorithm 20

Safe Human-Computer Interface Based On Efficient Image Proce...

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20th ieee International symposium on computational intelligence and Informatics (CINTI)

作者： Wilding, S. Walker, P. Clinton, S. Williams, D. Olszewska, J., I Univ Gloucestershire Cheltenham Glos England Univ West Scotland Glasgow Lanark Scotland

ISBN: (纸本)9781728183398

With the growing digitalization of our society and the increasing development of Industry 4.0, the development of safe human-computer interfaces is of prime importance. For this purpose, we present a new solution for avoiding any physical contact between the human and the machine's display and/or its keyboard/pad. Hence, we developed an innovative image processing algorithm which runs on the live video stream of the remote interaction between the human and the machine such as a computer or an intelligent agent;the video stream being captured by an off-the-shelf camera which is embedded in the main machine. The resulting computer-vision system performs visual object detection and tracking of a marker the user holds in one hand and could wave it from a distance in order to remotely interact with the interface of the machine. This remote interaction system has been successfully tested in real-world operational conditions, and the performance of this image processing application has been evaluated in real time.

关键词： Intelligent Vision Systems Man-Machine Systems Intelligent Agents Data processing image processing Safe Interface Industry 4.0

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Road Accident Black Spot Localisation using Morphological image processing Methods on Heatmap 18

Road Accident Black Spot Localisation using Morphological Im...

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18th ieee International symposium on computational intelligence and Informatics (CINTI)

作者： Szenasi, Sandor Felde, Imre Kertesz, Gabor Nadai, Laszlo Obuda Univ John von Neumann Fac Informat Budapest Hungary

ISBN: (纸本)9781728111179

Heatmaps are widely used by road safety engineers to visualise accident data (where heat refers to the concentration of accidents). In the subfield of road accident black spot localisation, the high number of similar black spot candidate locations makes this method unreliable and difficult to use. An additional process to convert the clusters of the heatmap into a list of black spot candidates results in an objective, comparable outcome. As we will show, the commonly used thresholding method (considering pixels above a given limit as parts of black spots) has several limitations. This paper presents a novel image processing approach to quantify the raw data of the heatmap. It is possible to give a more accurate splitting between black spot and safe areas, using the morphological function named erosion.

关键词： road safety accidents black spot heat map image processing convolution erosion

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Influence of signal pre-processing in the efficiency of algorithms based on neural networks for disturbance classification

Influence of signal pre-processing in the efficiency of algo...

引用

ieee symposium on computational intelligence in image and signal processing

作者： de Medeiros, Manoel F., Jr. Santos, Crisluci K. S. de Oliveira, Jose T. Pires, Paulo S. da M. de Melo, Jorge D. Doria Neto, Adriao D. Leitao, Jose J. A. L. Univ Fed Rio Grande do Norte DCA Natal RN Brazil CHESF Recife PE Brazil

ISBN: (纸本)9781424407071

Post dispatch analysis of signals obtained from digital disturbances registers provide important information to identify and classify disturbances in power systems, looking for a more efficient management of the supply. In order to enhance the task of identifying and classifying the disturbances - providing an automatic assessment - techniques of digital signal processing can be helpful. The Wavelet Transform has become a very efficient tool for the analysis of voltage or current signals, obtained immediately after disturbances occurrences in the network. This paper presents a methodology based on the Discrete Wavelet Transform to implement this process. It uses a comparison between distribution curves of signals energy, with and without disturbance. This is done for different resolution levels of its decomposition in order to obtain descriptors that permit its classification, using artificial neural networks.

关键词： Digital signal processing

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Study of Unsaturated Magnetic image processing in Wire Rope Aplication

Study of Unsaturated Magnetic Image Processing in Wire Rope ...

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10th International symposium on computational intelligence and Design (ISCID)

作者： Tan, Xiaojiang Zhang, Juwei Henan Univ Sci & Technol Coll Elect Engn Luoyang Peoples R China

ISBN: (纸本)9781538636749

Traditional magnetic flux leakage signal need be processed through each channels in magnetic array data, that increased processing system complexity. This paper proposed a processing system for unsaturated magnetic image, the processes included image transformation, filtering and resolution enhancement. This system overcame the shortcomings of interpolation method and digital signal processing. The experimental results showed that every defects could effectively be extracted and a good reconstruction image of multi-frame super-resolution was obtained with 3 simulated sampling intervals.

关键词： wire rope magnetic imageing image processing super-resolution

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A Small Targets Tracking Method for Water Mine Sonar image Array

A Small Targets Tracking Method for Water Mine Sonar Image A...

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5th International symposium on computational intelligence and Design (ISCID)

作者： Wang, Chao Jiang, Keyu Naval Univ Engn Dept Elect Engn Wuhan Peoples R China

ISBN: (纸本)9780769548111

Combining the static feature and the dynamic path in consecutive image array of small targets, this paper proposes a detecting method for small targets in sonar image: Improving the selection of (SRG) seeded region growing method, and defining the size of searching sub window, this paper realizes the selection of suspected targets in single image that have certain SRR (signal-to-reverberation ratio);to enhance the detection probability, we build the relative moving modal of vessel and targets, considering the shaking of vessel, obtain the searching limits and moving path of suspected targets in consecutive image array, and raise the principle of targets determination utilizing the IVF (intensity variation function). Experiment results show the validity of the algorithm

关键词： small target detection seeded region grow searching window target tracking

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Uniform Color Spaces Clustering in an Unsupervised Manner

Uniform Color Spaces Clustering in an Unsupervised Manner

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13th ieee International symposium on computational intelligence and Informatics (CINTI)

作者： Avraam, Marimpis Giorgos, Papadourakis Giorgos, Palamas Technol Educ Inst Crete Appl Informat & Multimedi Iraklion Greece

ISBN: (纸本)9781467352062;9781467352055

Color quantization is a critical task, frequently involved in image processing that reduces the number of distinct colors used in an image while retaining as much of the original representation capabilities. The key aspect here is to find the optimal palette and evaluate against unprocessed target images. The purpose of this paper is to compare the effectiveness of three well known unsupervised vector quantization algorithms (Neural Gas, Growing Neural Gas and Instantaneous Topological Map) in the field of color abstraction. Evaluation data for L*a*b* and L*u*v* uniform color spaces and a number of quality indices, exhibiting the performance in terms of overall quality, are presented.

关键词： image colour analysis image representation pattern clustering unsupervised learning vector quantisation

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An automatic wavelet-based approach for lung segmentation and density analysis in dynamic CT

An automatic wavelet-based approach for lung segmentation an...

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ieee symposium on computational intelligence in image and signal processing

作者： Talakoub, Omid Helm, Emma Alirezaie, Javad Babyn, Paul Kavanagh, Brian Grasso, Francesco Engelberts, Doreen Ryerson Univ Dept Elect & Comp Engn Toronto ON Canada Hosp Sick Children Dept Med Imaging Toronto ON Canada Univ Toronto Dept Med Imaging Toronto ON Canada Univ Waterloo Dept Syst Design Engn Waterloo ON N2L 3G1 Canada Hosp Sick Children Dept Crit Care Med Toronto ON Canada

ISBN: (纸本)9781424407071

Acute respiratory distress syndrome (ARDS) can occur in people with or without previous lung disease. Analysis of aeration in artificial ventilation for ARDS is one of the major applications of Computed Tomography (CT) lung density examination. A movie of an affected rabbit lung over the respiratory cycle was produced by dynamic CT with a cine loop technique. This technique can produce thousands of CT images for analysis with a single experiment. A fully automated algorithm based on the capability of wavelet transformation to detect edges in the image is proposed. This method accurately and consistently segments the lung in pulmonary CT images. The speed and accuracy of this technique allows it to outperform other methods when dealing with the large number of images created by dynamic Computed Tomography.

关键词： image segmentation

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A computational Algorithm Based on Convolutional Neural Networks Aimed at Estimating the MOS Quality Parameter According to the Norm UIT-T P.862 22

A Computational Algorithm Based on Convolutional Neural Netw...

引用

22nd symposium on image, signal processing and Artificial Vision (STSIVA)

作者： Gutierrez, Rodrigo Asca, Brallan Kemper, Guillermo Univ Peruana Ciencias Aplicadas Sch Elect Engn Fac Engn Lima Peru

ISBN: (纸本)9781728114910

This paper proposes an algorithm based on convolutional neural networks for the estimation of the quality level of voice signals transmitted through cellular communication systems. The objective is to take advantage of artificial intelligence methods to estimate the MOS parameter and obtain a similar accuracy to that obtained by methods and procedures established in the international norms and international licensed standards. The proposed algorithm uses the MOS results obtained by the method detailed in the ITU-T P.862 standard. The values were obtained for different signals acquired at different reception points. With this information we proceeded to design and train a convolutional neuronal network of 4 layers, achieving very satisfactory results. For the validation, the mean square error was used to measure the degree of similarity of the MOS values obtained by ITU-T P.862 and by the proposed algorithm. The results show a mean square error of 0.00007 for the proposed algorithm.

关键词： Convolutional neural network MOS PESQ UIT-T P.862 QoE

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Explainability of deep learning models in medical image classification 22

Explainability of deep learning models in medical image clas...

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ieee Joint 22nd International symposium on computational intelligence and Informatics / 8th ieee International Conference on Recent Achievements in Mechatronics, Automation, Computer Science and Robotics (CINTI-MACRo)

作者： Kolarik, Michal Sarnovsky, Martin Paralic, Jan Butka, Peter Tech Univ Kosice FEI Dept Cybernet & Artificial Intelligence Kosice Slovakia

ISBN: (纸本)9798350398823

The ability to explain the reasons for one's decisions to others is an important aspect of being human intelligence. We will look at the explainability aspects of the deep learning models, which are most frequently used in medical image processing tasks. The Explainability of machine learning models in medicine is essential for understanding how the particular ML model works and how it solves the problems it was designed for. The work presented in this paper focuses on the classification of lung CT scans for the detection of COVID-19 patients. We used CNN and DenseNet models for the classification and explored the application of selected visual explainability techniques to provide insight into how the model works when processing the images.

关键词： Deep learning explainability XAI image classification

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