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A Multi-Level Thresholding image Segmentation Based on an Improved Artificial Bee Colony Algorithm 2nd

A Multi-Level Thresholding Image Segmentation Based on an Im...

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2nd EAI International Conference on Robotic Sensor Networks, ROSENET 2018

作者： Xia, Xingyu Gao, Hao Hu, Haidong Lan, Rushi Pun, Chi-Man The Institute of Advanced Technology Nanjing University of Posts and Telecommunications Nanjing China Department of Computer and Information Science University of Macau China Beijing Institute of Control Engineering Beijing China Key Laboratory of Intelligent Processing of Computer Image and Graphics Guilin University of Electronic Technology Guilin China

ISBN: (纸本)9783030177621

As a popular evolutionary algorithm, artificial bee colony (ABC) algorithm has been successfully applied into the threshold-based image segmentation problem. Based on our analysis, we find that the Otsu segmentation function is separable which means each variable is independent. Due to its one-dimensional search strategy and relative power global but poorer local search abilities, ABC could find an acceptable but not precise segmentation results. For making more precise search and further enhancing the achievements on image segmentation, we propose an Otsu segmentation method based on a new ABC algorithm with an improved scout bee strategy. Different from the traditional scout bee strategy, we use a local search strategy when a bee stagnates for a defined value. The experimental results on Berkeley segmentation database demonstrate the effectiveness of our algorithm. © 2020, Springer Science and Business Media Deutschland GmbH. All rights reserved.

关键词： image segmentation

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AUTOMATED FABRIC INSPECTION BASED ON A STRUCTURAL TEXTURE ANALYSIS METHOD

AUTOMATED FABRIC INSPECTION BASED ON A STRUCTURAL TEXTURE AN...

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SATELLITE CONF AT THE 1988 BIANNUAL INTERNATIONAL CONF ON PATTERN RECOGNITION : RECENT ISSUES IN PATTERN ANALYSIS AND RECOGNITION

作者： TUFIS, I International Basic Laboratory for Image Processing and Computer Graphics Central Institute for Cybernetics and Information Processes Kurstr. 33 P.O.B. 1298 Berlin Germany Department of Robotics and Real Time Systems Research Institute for Computer Technique and Informatics B-dul Miciurin 8-10 Bucharest 1 71316 Romania

ISBN: (纸本)0387518150

An approach for applying a structural texture analysis method to automatic visual inspection of fabric samples in the textile industry is presented. The main steps (image preprocessing, image segmentation, model description and matching) to accomplish this task are described and also some conclusions are drawn from the preliminary experiments. © 1989, Springer-Verlag.

关键词： image segmentation

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Enhancing Security in Smart Homes with IoT Using Logit-Boosted Techniques 6

Enhancing Security in Smart Homes with IoT Using Logit-Boost...

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6th International Conference on computer Information Science and Application Technology, CISAT 2023

作者： Rahim, Asif Zhong, Yanru Ahmad, Tariq School of Computer and Information Security Guilin university of Electronic Technology Guilin54001 China Guangxi Key Laboratory of Intelligent Processing of Computer Image and Graphics Guilin University of Electronic Technology Guilin541001 China School of Information and Communication Engineering Guilin University of Electronic Technology Guilin541001 China

ISBN: (纸本)9781510668546

The utilization and advancement of Internet of Things (IoT) gadgets have noticeably increased in recent times. Various sectors, including intelligent homes, healthcare, sports analysis, and different industries, use IoT devices. Traffic is a crucial aspect of IoT devices, and it differs from conventional device traffic in several ways. This investigation employed 41 Internet of Things (IoT) devices. A machine learning model was developed that can classify IoT devices into multiple categories based on 13 different network traffic features. The raw data that was gathered was preprocessed using techniques like standardization and scaling techniques of the dataset. Algorithms for feature selecting can be utilized to extract characteristics from textual data. Following stratification, The dataset contains 106,234 sets of features that were utilized to enhance the predictive model. This research employed various evaluation metrics to demonstrate the effectiveness of the logistic-boosted algorithms. In this research, collaborative machine learning methods were utilized as a starting point to develop an intrusion detection system (IDS) that can identify abnormal network traffic. The principal aim of this investigation is to identify attacks and abnormalities within a Smart Home IoT setting. We have introduced a new technique for constructing Logit-Boosted algorithm, namely Logi-CatBoost Classifier. Once the logitboosted algorithm was employed to classify the dataset, Logi-CBC performed the best, with an accuracy of 88.70%. We suggested Logi-CBC algorithm achieved the top precision among previously used Logit-Boosted algorithms in past studies on the same dataset. © 2023 SPIE.

关键词： Internet of things

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Report on AUSGRAPH '90, the 1990 Australian graphics Conference Melbourne, 10–14 September 1990

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computer graphics Forum 1990年第5期9卷 389-389页

作者： Maeder, Anthony Computer Graphics and Image Processing Research Laboratory Department of Computer Science Monash University Clayton 3168 Australia

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Learning a nonlinear color distance metric for the identification of skin immunohistochemical staining

Learning a nonlinear color distance metric for the identific...

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2009 22nd IEEE International Symposium on computer-Based Medical Systems, CBMS 2009

作者： Sobieranski, Antonio Carlos Neto, Sylvio Luiz Mantelli Coser, Leandro Comunello, Eros Von Wangenheim, Aldo Cargnin-Ferreira, Eduardo Di Giunta, Gabriella LAPIX Laboratory of Image Processing and Computer Graphics UFSC Federal University of Santa Catarina Brazil CPTEC Center for Weather Forecasts and Environment Studies INPE - Brazilian Institute for Space Research Brazil EGC Knowledge Engineering Department UFSC - Federal University of Santa Catarina Brazil MCA Graduate Program in Applied Computer Science UNIVALI - Itajai Valley University Brazil Laboratory of Histological Markers Department of Biology Embriology and Genetics UFSC - Federal University of Santa Catarina Brazil Pathology Service UFSC - Federal University of Santa Catarina Brazil

ISBN: (纸本)9781424448784

This paper presents a semiautomatic method for the identification of immunohistochemical (IHC) staining in digitized samples. The user trains the system by selecting on a sample image some typical positive stained regions that will be used as a reference for the construction of a distance metric. In this learning process, the global optimum is obtained by induction employing higher polynomial terms of the Mahalanobis distance, extracting nonlinear features of the IHC pattern distributions. The results of the proposed method showed a high correlation to a pathologist's manual analysis, which was used as a golden standard, presenting a more robust discrimination between stained and non-stained areas with little bias. © 2009 IEEE.

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Real-Time 6-DoF Object Pose Estimation Network Based on 2D-3D Coordinate Correspondence 3rd

Real-Time 6-DoF Object Pose Estimation Network Based on 2D-3...

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3rd International Conference on Artificial Intelligence, Robotics, and Communication, ICAIRC 2023

作者： Li, Shuai Chen, Jinlong Yang, Minghao Su, Jianhua Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guangxi Guilin541004 China Key Laboratory of Intelligent Processing of Computer Image and Graphics Guilin University of Electronic Technology Guangxi Guilin541004 China Beijing100190 China HuaiRou Beijing101400 China Beijing100190 China

ISBN: (纸本)9789819721993

Object 6D pose estimation is essential for a variety of applications, including autonomous driving, robotic manipulation, and automated harvesting. Due to the influence of different lighting conditions and occlusions, objects with different poses may exhibit significant variations in appearance in different views. This makes the estimation of the 6D pose of objects from a single RGB image a challenging task. This paper proposes a deep learning network capable of simultaneously detecting and estimating the 6D pose (3D rotation + 3D translation) of target objects. As establishing a large-scale dataset using real data is extremely challenging, this paper introduces an automatic collection scheme based on virtual data generated from real images. We conducted experiments on the generated astronaut dataset using our data collection scheme for 6D pose estimation. The experimental results show that the accuracy of 6D pose estimation based on the ADD metric is 96%. Therefore, this method has significant potential and can be extended to other downstream tasks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Deep learning

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A Web-Based Tool for Semi-Automated Segmentation of Histopathological images Using Nonlinear Color Classifiers

A Web-Based Tool for Semi-Automated Segmentation of Histopat...

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Annual IEEE Symposium on computer-Based Medical Systems

作者： Marcelo Dornbusch Lopes Antonio C. Sobieranski Aldo Von Wangenheim Eros Comunello INCoD - National Brazilian Institute for Digital Convergence / LAPIX - Image Processing and Computer Graphics Lab - Federal University of Santa Catarina Brazil Postgraduate Program in Applied Computing University of Itajai Valley - UNIVALI INCoD (Nat. Brazilian Inst. for Digital Convergence) LAPIX (Image Process. & Comput. Graphics Lab.) Universidade Federal de Santa Catarina Florianopolis SC BR

ISBN: (纸本)9781467390378

Histopathological staining is a technique widely used to highlight biological states or pharmacological activities in uman tissue. A quantitative analysis of the resulting images can produce biomarkers for diseases or even other specific conditions, thus providing valuable information for diagnosis and prognosis. Since biomarkers require measurements to be made in an objective and consistent way, software systems are employed to provide this quantitative analysis. For measurements to be reproducible, the same methods must be available across different laboratories. In this paper, we present a tool that allows users to perform quantitative analyses over the web, thus providing an efficient environment not only for individual cases to be evaluated, but also for users to share a common ground when making measurements. The classification method used by the tool to segment stained pixels is performed by a similarity function based on the polynomial version of the Mahalanobis distance, which is nonlinear and provides very robust classification for m-dimensional feature spaces. Furthermore, the similarity function can be generalized in the tool, so that images can be classified by reusing parameters of previous cases. The results of our web-based approach were compared with established ground-truth data sets, producing sensitivity, specificity and fitness values of 97.09%, 98.70%, and 97.90%.

关键词： image color analysis image segmentation Biomarkers Sensitivity Inspection Servers Statistical analysis

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Linear programming concept visualization

Linear programming concept visualization

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International Conference on Information Visualisation (IV)

作者： J.P. Charalambos E. Izquierdo Image Processing and Computer Graphics Research Laboratory Department of Computer Sciences National University Colombia Department of Electronic Engineering Queen Mary University of London London UK

A visualization scheme as a tool to find the solution of any 3D-linear programming problem is introduced. The presented approach is highly suitable to draw and visualize interactively the feasible region of a given 3D-linear programming problem. It can be used for a better understanding of the solution process when different methods devoted to solve the underlying problem are applied, e.g., the simplex method. The proposed technique comprises sensitive analysis during the solution process and interactive visualization of the feasible region. The analysis leading to the introduced schema also shows that the design of an appropriate and simple vertex representation is crucial to manage any order of degeneracy. To deal with this paradigm and to some extent to formalize it, the concept of adjacency invariance is introduced. Several experiments have been conducted to test and assess the performance of the introduced concepts and techniques.

关键词： Linear programming Visualization Testing computer graphics image processing Appropriate technology Stress Algorithm design and analysis

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An extended probabilistic collaborative representation based classifier for image classification

An extended probabilistic collaborative representation based...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Rushi Lan Yicong Zhou Key Laboratory of Intelligent Processing of Computer Image and Graphics Guilin University of Electronic Technology Guilin China Department of Computer and Information Science University of Macau Macau China

ISBN: (纸本)9781509060689

Collaborative representation based classifier (CRC) and its probabilistic improvement ProCRC have achieved satisfactory performance in many image classification applications. They, however, do not comprehensively take account of the structure characteristics of the training samples. In this paper, we present an extended probabilistic collaborative representation based classifier (EProCRC) for image classification. Compared with CRC and ProCRC, the proposed EProCRC further considers a prior information that describes the distribution of each class in the training data. This prior information enlarges the margin between different classes to enhance the discriminative capacity of EProCRC. Experiments on two challenging databases, namely CUB200-2011 and Caltech-256, are conducted to evaluate EProCRC, and comparison results demonstrate that it outperforms several state-of-the-art classifiers.

关键词： Training Collaboration Probabilistic logic Training data Feature extraction Databases Robustness

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FAST ALGORITHM FOR COMPUTING FRACTAL DIMENSIONS OF image SEGMENTS

FAST ALGORITHM FOR COMPUTING FRACTAL DIMENSIONS OF IMAGE SEG...

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SATELLITE CONF AT THE 1988 BIANNUAL INTERNATIONAL CONF ON PATTERN RECOGNITION : RECENT ISSUES IN PATTERN ANALYSIS AND RECOGNITION

作者： CREUTZBURG, R IVANOV, E Central Institute of Cybernetics and Information Processes International Basic Laboratory for Image Processing and Computer Graphics Academy of Sciences of the G.D.R. Kurstr. 33 P. O. Box 1298 Berlin DDR - 1086 Germany Department of Information Techniques University of Technology Mommsenstr. 13 Dresden DDR - 8027 Germany

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