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High Performance Big Data and Intelligent systems (HPBD&IS)

作者： Huijuan Zhang Xuezhong Xiao School of Computer Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (数字)9781728165127

ISBN: (纸本)9781728158976

image watercolorization is a hot research topic in the field of non-photorealistic rendering. There are many methods proposed to simulate the various features of watercolor painting including edge darkening, pigment dispersion, turbulence, and paper texture. However, almost all of them are implemented for desktop systems and cannot be directly transplanted to mobile devices. From the view of resultant effects and computing efficiency, an image watercolorization framework is proposed for smart phones, which employs several existing image processing algorithms to simulate the visual features of watercolor painting. Finally, the method is optimized in parallel to improve the efficiency. The experiments show the presented method has good performance.

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Infrared Dim and Small Targets Detection Based on Multi-scale Local Contrast Measure Utilizing Efficient Spatial Filters

Infrared Dim and Small Targets Detection Based on Multi-scal...

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International conference of Signal processing and Intelligent systems (ICSPIS)

作者： Iman Faramarzi Jinhui Han Yuanyuan Chen Faculty of Electrical and Computer Engineering Malek-e-Ashtar University of Technology Tehran Iran College of Physics and Telecommunication Engineering Zhoukou Normal University Zhoukou China

ISBN: (数字)9781728186290

ISBN: (纸本)9781728186306

Given the growing importance of infrared search and track (IRST) systems, in this paper, inspired by the mechanism of the human visual system (HVS), we present a robust algorithm for the detection of infrared (IR) dim and small targets based on Multi-scale Local Contrast Measure utilizing Efficient Spatial Filters, which is named as ESFMLCM. In the proposed algorithm by considering a nested structure, three efficient spatial filters, namely Gaussian filter, mean filter, and standard deviation filter, are applied to each pixel of the raw IR image, simultaneously. According to the idea of the matched filter, the Gaussian filter has been used to improve the actual targets and increase the detection rate. Also, two other filters have been used to suppress all the types of interferences (noise and background clutters) and reduce the false alarm rate. Finally, a simple adaptive threshold operation is applied to extract actual targets or remove fake targets. The numerical and visual results show that the proposed algorithm can detect IR dim and small targets under complex backgrounds with high accuracy in comparison with other algorithms.

关键词： Matched filters visualization Signal processing algorithms Filtering algorithms Spatial filters Clutter Standards

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Secured Automated Complaint Generation System for Organizations

Secured Automated Complaint Generation System for Organizati...

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International conference on Computer, Communication and Signal processing (ICCCSP)

作者： K vidya Lavanya Amalbabu K.S Sowndharya Swaathi Balaji College of Engineering Anna University Chennai India

ISBN: (数字)9781728165097

ISBN: (纸本)9781728165103

In our society, complaint systems are all done manually by humans and there are no automated system wherein the complaints are identified and sent to the respective authority all by itself. A complaint about our day to day activities based on the images can be identified and given as a report. This reduces lot of manual time and may speedup the remedial process. In this system, the users need to upload an image which will be analyzed and classified based on remedial departments. Thus the amount of manual work both on the user and the organization is minimized by feasibly producing an automated system that can generate a report about the problem without human intervention during the process. Based on the institutional requirements, the complaints are classified as website-based and object-based using an image classification system. The web-related complaints are handled by optical character recognition and the object-based complaints are handled by object detection and data mining techniques. The images are trained and tested through various classification system and their performances are compared. The user is also provided with a feature of adding location along with the complaint image which makes less complication in finding the place of fault and based on which a report is generated and forwarded to corresponding department. Thus, this paper aims in proposing an automated complaint generation and reporting system for Institutions by classifying user input images using image processing and data mining techniques.

关键词： Feature extraction Training Object detection Computational modeling Proposals Signal processing algorithms Classification algorithms

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Modeling of Intelligent systems Architecture Based on the Brain Topology 14th

Modeling of Intelligent Systems Architecture Based on the Br...

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14th International conference on Pattern Recognition and Information processing (PRIP)

作者： Baranovski, Oleg Krasnoproshin, viktor Valvachev, Alexander Belarusian State Univ Nezavisimosti Ave 4 Minsk BELARUS

ISBN: (纸本)9783030354305;9783030354299

The article presents the results of the unification of the architecture of computer intelligent systems based on the topology of the functional systems of the human brain intelligence. A pragmatic conceptual framework is proposed that eliminates the polysemy characteristic of this area, a set of models and algorithms is developed that unifies and standardizes the decision-making process. As part of the multi-agent approach, a special unified system architecture and the corresponding program library were developed and implemented. The effectiveness of the approach is demonstrated by an example of solving an applied problem.

关键词： Intelligent systems Ultra large scale systems Decision making Monitoring systems Program agents

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image Color Reduction Using Progressive Histogram Quantization and Kmeans Clustering

Image Color Reduction Using Progressive Histogram Quantizati...

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Mechatronics, Remote Sensing, Information systems and Industrial Information Technologies (ICMRSISIIT), International conference on

作者： Ibrahim El rube’ Taif University Taif KSA

ISBN: (纸本)9781728104874

Color reduction is an important tool for different image processing and computer vision applications. In this paper, a progressive histogram-based color reduction (quantization) is used with the Kmeans clustering algorithm to speed up the quantization process of the Kmeans method. The progressive histogram quantization (PHQ) is a simple iterative algorithm where a single histogram bin is merged to one of its two nearest neighbors' bins at each iteration. The histogram bin is merged according to the differences in the value (pixel counts) and the location of the left and right bins. The PHQ algorithm is used as a pre-quantization for the Kmeans clustering to reduce the size of the data and speed up the clustering process. The experimental results show that the PHQ+Kmeans algorithm maintains good image quality and enhances the execution time compared to the Kmeans clustering algorithm alone when applied on remote sensing images.

关键词： image quality Histograms Quantization (signal) Mechatronics image color analysis Clustering algorithms Tools

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3rd International conference on Computational Intelligence and Informatics, ICCII 2018

3rd International Conference on Computational Intelligence a...

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3rd International conference on Computational Intelligence and Informatics, ICCII 2018

ISBN: (纸本)9789811514791

The proceedings contain 79 papers. The special focus in this conference is on Computational Intelligence and Informatics. The topics include: Click-through rate prediction using decision tree;a new framework approach to predict the wine dataset using cluster algorithm;study and ranking of vulnerabilities in the indian mobile banking applications using static analysis and bayes classification;analysis of object identification using quadrature bank filter in wavelet transforms;experimental analysis of the changes in speech while normal speaking, walking, running, and eating;uip—a smart web application to manage network environments;energy distribution in a smart grid with load weight and time zone;matrix approach to perform dependent failure analysis in compliance with functional safety standards;a cloud-based privacy-preserving e-healthcare system using particle swarm optimization;improved approach to extract knowledge from unstructured data using applied natural language processing techniques;word sense disambiguation in telugu language using knowledge-based approach;a study of digital banking: Security issues and challenges;encoding approach for intrusion detection using pca and knn classifier;materializing block chain technology to maintain digital ledger of land records;review of optimization methods of medical image segmentation;automatic temperature control system using arduino;performance analysis of fingerprint recognition using machine learning algorithms;a survey on digital forensics phases, tools and challenges;a brief survey on blockchain technology;energy-efficient based multi-path routing with static sink using fuzzy logic controller in wireless sensor networks;mst parser for telugu language;design of low-power vedic multipliers using pipelining technology;needleman–wunsch algorithm using multi-threading approach;quicksort algorithm—an empirical study.

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Convolutional neural networks application in cardiovascular decision support systems 2

Convolutional neural networks application in cardiovascular ...

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2nd International conference on image and video processing, and Artificial Intelligence (IPVAI)

作者： Natalia, Konnova Mikhail, Basarab Michael, Khachatryan Anna, Domracheva Igor, Ivanov Bauman Moscow State Tech Univ Comp Sci & Control Syst Dept 2 Ya Baumanskaya St5 Moscow 105005 Russia

ISBN: (数字)9781510634107

ISBN: (纸本)9781510634107

The paper considers the possibilities of using neural network methods of machine learning to diagnose the states of the human cardiovascular system and support decision-making in cardiology and cardiac surgery. The issues of processing and preparation of electrocardiography signals, selection of architecture and tuning of neural network parameters for automation of diagnosis are discussed. Here, the results obtained with the help of multilayer perceptrons and convolutional neural networks to assign the submitted input cardiovascular data to one of the classes of states in the selected space are examined. Based on a specialized developed software, the proprietary numerical experiments with real clinical data were carried out. Given the above results, demonstrating the applicability of the used deep learning methods and algorithms to diagnostic automation, a model of a hierarchical decision support system is proposed.

关键词： decision support system deep learning digital signal processing machine learning neural networks

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An image retrieval system using an artificial neural network for the identification and classification of lung diseases

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AIP conference Proceedings 2025年第1期3254卷

作者： Atul Pratap Singh Ajeet Singh Amit Kumar Hari Om Sharan C. S. Raghuvanshi Department of AI Noida Institute of Engineering and Technology Greater Noida UP India Dept of CSE Moradabad Institute of Technology Moradabad UP India Dept of CSE FET Rama University Kanpur UP India

Automated systems for lung disease identification and classification are being developed with quick pace, thanks to the rapid advancements in the field of Medical Imaging Technologies. This paper describes the latest development and application of a novel Artificial Neural Network (ANN)-based image retrieval system to improve the precision and efficacy in terms of lung disease diagnosis. The approach under consideration is designed to tackle the difficulties involved in accurately identifying and categorizing lung disorders using medical imaging, including CT and X-rays. By utilizing Artificial Neural Networks (ANNs), more especially convolutional neural networks (CNNs), the system seeks to identify complex patterns and features in the images that are frequently invisible to the human observers. This makes it possible for the system to pick up on discriminative representations of both healthy lung structure and different disease states. There are several steps involved in the system’s design. First, a large collection of annotated lung photos is assembled, including a wide variety of lung conditions and the associated healthy states. A pre-processing pipeline is then put into place to standardize the images, guaranteeing a constant quality and making feature extraction easier. Then, in order to enable efficient learning and classification, the CNN architecture is painstakingly built, paying close attention to layer configurations, activation functions, and optimization techniques. Additionally, the system uses image retrieval algorithms, which allow for the effective search and retrieval of pertinent medical images from the database in response to query inputs. In order to promote appropriate diagnosis and treatment planning, this retrieval functionality helps medical practitioners locate similar cases for comparative study and reference. Comprehensive tests are carried out utilizing benchmark datasets to assess the system’s performance, and metrics including accura

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IQ-STAN: image Quality Guided Spatio-Temporal Attention Network for License Plate Recognition

IQ-STAN: Image Quality Guided Spatio-Temporal Attention Netw...

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IEEE International conference on Acoustics, Speech and Signal processing

作者： Cong Zhang Qi Wang Xuelong Li School of Computer Science and Center for OPTical IMagery Analysis and Learning (OPTIMAL) Northwestern Polytechnical University Xi’an P. R. China

ISBN: (数字)9781509066315

ISBN: (纸本)9781509066322

License plate recognition (LPR) is one of the essential components in intelligent transportation systems. Although the image processing algorithms for LPR have been extensively studied in the past several years, the recognition performance is still not satisfactory especially in unconstrained complex scenes. In order to tackle this issue, a novel deep multi-task learning-based method is proposed in this paper by introducing contextual information in multiple license plate frames. Specifically, an end-to-end trainable multi-task architecture, namely IQ-STAN, is developed by joint license plate recognition and image quality scoring. Moreover, we propose an image quality-guided spatio-temporal attention mechanism, which is utilized in the frame-level feature representation during the phase of plate recognition. Extensive experiments are conducted and the competitive results demonstrate the effectiveness of our proposed framework.

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Machine Learning in Information visualization: Using Rule-based Learning algorithms to Personalize Interfaces

Machine Learning in Information Visualization: Using Rule-ba...

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International conference on systems, Signals and image processing, IWSSIP

作者： Leonardo Souza Silva Ricardo Nakamura Fatima L. S. Nunes Interactive Technologies Laboratory Escola Politécnica Universidade de São Paulo São Paulo Brasil Laboratory of Computer Applications for Health Care Escola de Artes Ciências e Humanidades Universidade de São Paulo São Paulo Brasil

ISBN: (数字)9781728175393

ISBN: (纸本)9781728175409

Machine Learning has offered great potential in areas such as data mining and information retrieval, while less attention has been given to its use in the design of Information visualization tools. Based on user needs, a properly designed interface can enhance augmented perception; however, the project is usually conducted without the inclusion of users. Machine Learning techniques can be useful to promote the users' involvement in the interface development process, contributing to offer personalized visualizations. Based on a dataset from a User Experience experiment with an interactive 3D environment to visualize medical temporal data, we present an approach using rule-based learning algorithms to promote the user's involvement. Our results indicate that Association Rule Learning can be a valuable resource to improve the design of Information visualization interface tools as well as to customize visualization according to the user's preferences.

关键词： Data visualization image color analysis Tools visualization Itemsets Three-dimensional displays Shape

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