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检索条件"任意字段=17th Image Processing: Algorithms and Systems Conference, IPAS 2019"

共 249 条记录，以下是131-140 订阅

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Development of a Procedure for Improving the Effectiveness of Personal Identification systems Based on the Analysis of Facial images 17

Development of a Procedure for Improving the Effectiveness o...

引用

17th International Scientific and Technical conference on Dynamics of systems, Mechanisms and Machines, Dynamics 2023

作者： Tatarkanov, A.A. Umyskov, A.A. Kuklin, V. Zh. Institute of Design and Technology Informatics of RAS Moscow Russia

ISBN: (纸本)9798350358315

this research aims to develop a new procedure to improve the performance of the personal identification system. this process will be based on the analysis of digital facial images using special artificial intelligence technologies. Additionally, it is emphasized that the successful development of a completely new neural network algorithm for personality identification and its special robust modification are required to achieve this goal. Furthermore, it is essential that this algorithm demonstrates increased effectiveness in identifying faces. As part of this algorithm, two key components are distinguished, namely, an algorithm aimed at determining the area where a face is located in an image, which involves the use of a standard version of a convolutional neural network. And the presented neural network algorithm is the second component, which is designed for personal identification with a specific robust modification. the studies presented have shown that an algorithm with a proposed architecture, will have around 25 times less weight parameters than the algorithms utilized at present. Also, unlike other algorithms, it was possible to improve the level of accuracy. © 2023 IEEE.

关键词： image enhancement

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the Self-calibration Parameter Generating Device of Workpiece processing Based on Machine Vision 17th

The Self-calibration Parameter Generating Device of Workpiec...

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17th Chinese Intelligent systems conference, CISC 2021

作者： Wang, Zhenqi Guo, Dong Qin, Weier Gong, Rui School of Electrical Engineering Liaoning University of Technology Jinzhou121001 China School of Machinery Branch Liaoning Vocational University of Technology Jinzhou121007 China

ISBN: (纸本)9789811663192

this design is based on the machine vision measurement technology to measure the precise size of the workpiece produced in the factory assembly line. the Raspberry Pi 4B is used as the controller, and the image is collected by the camera mounted at the bottom of the z-axis of the three-axis slide platform. the image information is reduced by image preprocessing algorithm to reduce the environmental noise of the image. Again by feature extraction and feature fitting method to image edge locating and fitting, and then through the size transform algorithm to get the size measurement, the measurement data with the workpiece design dimension data generated from the calibration parameters analysis table, through the Profibus bus transfer to processing equipment, complete processing equipment for processing the product feedback. © 2022, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Computer vision

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A Slightly Supervised Approach for Positive/Negative Classification of Fluorescence Intensity in HEp-2 images

A Slightly Supervised Approach for Positive/Negative Classif...

引用

17th International conference on image Analysis and processing (ICIAP)

作者： Iannello, Giulio Onofri, Leonardo Soda, Paolo Univ Campus Biomed Roma Integrated Res Ctr Comp Sci & Bioinformat Lab Rome Italy

ISBN: (纸本)9783642411847;9783642411830

Indirect Immunofluorescence on HEp-2 slides is the recommended technique to detect antinuclear autoantibodies in patient serum. Such slides are read at the fluorescence microscope by experts of IIF, who classify the fluorescence intensity, recognize mitotic cells and classify the staining patterns for each well. the crucial need of accurately performed and correctly reported laboratory determinations has motivated recent research on computer-aided diagnosis tools in IIF to support the HEp-2 image classification. Such systems adopt a fully supervised classification approach and, hence, their chance of success depends on the quality of ground truth used to train the classification algorithms. Besides being expensive and time consuming, collecting a large and reliable ground truth in IIF is intrinsically hard due to the inter-and intra-observer variability. In order to overcome such limitations, this paper presents a slightly supervised approach for positive/negative fluorescence intensity classification. the classification phase consists in matching parts of interest automatically detected in the test image with a Gaussian mixture model built over few control images. the approach, whose operating configuration can be adapted to the cost of misclassifications, has been tested over a database with 914 images acquired from 304 different wells, achieving remarkable results on positive/negative screening task.

关键词： image classification

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Artificial Intelligence in Medicine 1

引用

丛书名： Lecture Notes in Computer Science

1000年

作者： David Riaño Szymon Wilk Annette ten Teije

ISBN: (数字)9783030216429

ISBN: (纸本)9783030216412

this book constitutes the refereed proceedings of the 17th conference on Artificial Intelligence in Medicine, AIME 2019, held in Poznan, Poland, in June 2019.;the 22 revised full and 31 short papers presented were carefully reviewed and selected from 134 submissions. the papers are organized in the following topical sections: deep learning; simulation; knowledge representation; probabilistic models; behavior monitoring; clustering, natural language processing, and decision support; feature selection; image processing; general machine learning; and unsupervised learning.

关键词： Artificial Intelligence Information systems and Communication Service Computer systems Organization and Communication Networks Computer Imaging, Vision, Pattern Recognition and Graphics Computer Applications Probability and Statistics in Computer Science

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Human-Computer Interaction – INTERACT 2019 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： David Lamas Fernando Loizides Lennart Nacke Helen Petrie Marco Winckler Panayiotis Zaphiris

the four-volume set LNCS 11746–11749 constitutes the proceedings of the 17th IFIP TC 13 International conference on Human-Computer Interaction, INTERACT 2019, held in Paphos, Cyprus, in September 2019.

ISBN: (数字)9783030293840

ISBN: (纸本)9783030293833

关键词： User Interfaces and Human Computer Interaction Information systems Applications (incl. Internet) image processing and Computer Vision Special Purpose and Application-Based systems Computer Communication Networks Artificial Intelligence

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Human-Computer Interaction – INTERACT 2019 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： David Lamas Fernando Loizides Lennart Nacke Helen Petrie Marco Winckler Panayiotis Zaphiris

ISBN: (数字)9783030293871

ISBN: (纸本)9783030293864

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Dynamic Environment Optimization Algorithm Based on Dynamic Lion Swarm Algorithm and Its Implementation 17

Dynamic Environment Optimization Algorithm Based on Dynamic ...

引用

17th IEEE International conference on Signal processing, ICSP 2024

作者： Wang, Feng Jiang, Mingyan Jiang, Keqin An, Xianxu Zhao, Ze Shandong University Dept. School of Information Science and Engineering QingDao China

ISBN: (纸本)9798350387384

In the information age, many practical problems involve dynamic objective functions that change over time or due to other factors. Optimizing in such dynamic environments is crucial both theoretically and practically, as it addresses prominent challenges in optimization today. For instance, dynamic vehicle path planning requires adapting to changing vehicle and road conditions to determine the optimal route. In image processing, dynamic multi-objective segmentation can enhance recognition accuracy by addressing changing image data. In engineering, designing dynamic welded beams involves adjusting for changes in material properties over time. Traditional lion swarm optimization (LSO) algorithms often struggle with dynamic environments, tending to optimize based on outdated conditions and missing global optimal solutions. this paper improves LSO by incorporating dynamic particle swarm optimization mechanisms and the black-winged kite algorithm's hunting and elimination strategies to better track global optima in changing environments. the performance of the improved dynamic lion swarm algorithm is evaluated using the four-peak DF1 dynamic environment model, enhanced by the bimodal DFI model. © 2024 IEEE.

关键词： image segmentation

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Measuring camera shannon information capacity with a siemens star image 17

Measuring camera shannon information capacity with a siemens...

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17th image Quality and System Performance conference, IQSP 2020

作者： Koren, Norman L. Imatest LLC BoulderCO United States

Shannon information capacity, which can be expressed as bits per pixel or megabits per image, is an excellent figure of merit for predicting camera performance for a variety of machine vision applications, including medical and automotive imaging systems. Its strength is that is combines the effects of sharpness (MTF) and noise, but it has not been widely adopted because it has been difficult to measure and has never been standardized. We have developed a method for conveniently measuring information capacity from images of the familiar sinusoidal Siemens Star chart. the key is that noise is measured in the presence of the image signal, rather than in a separate location where image processing may be different-a commonplace occurrence with bilateral filters. the method also enables measurement of SNRI, which is a key performance metric for object detection. Information capacity is strongly affected by sensor noise, lens quality, ISO speed (Exposure Index), and the demosaicing algorithm, which affects aliasing. Information capacity of in-camera JPEG images differs from corresponding TIFF images from raw files because of different demosaicing algorithms and nonuniform sharpening and noise reduction. © 2020 Society for Imaging Science and Technology.

关键词： Object detection

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A Methodology Based on Unsupervised Learning Techniques to Identify the Degree of Food processing 17

A Methodology Based on Unsupervised Learning Techniques to I...

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17th Iberian conference on Information systems and Technologies, CISTI 2022

作者： Marcos, Ignacio Fernández-Villacañas Bordel, Borja Cira, Calimanut-Ionut Alcarria, Ramón Universidad Politécnica de Madrid Madrid Spain

ISBN: (纸本)9789893334362

the level of consumption of processed foods is increasing globally, with a consequent impact on long-term human health due to the increasingly common diseases related to the metabolic syndrome. therefore, to prevent the continuous spread of these diseases, it is a need to accurately identify the degree of processing of different types of food. there are already several systems that provide rules to classify the level of processing. such as NOVA, but their limitations usually require that nutrition experts follow already established criteria to manually carry out the classification. In this work, we propose a methodology based on unsupervised learning to create food clusters that correspond to their level of processing. In this regard, we apply unsupervised machine learning algorithms to generate food clusters based on their nutritional properties. Training data were retrieved from the Food and Nutrient Database for Dietary Studies (FNDDS). the application of the proposed methodology allowed the differentiation of foods according to their level of processing with an acceptable level of performance. In the end, the proposed methodology is applied to another dataset containing nutrition information from a very large list of real recipes in order to estimate the rate of ultra-processed recipes. © 2022 IEEE Computer Society. All rights reserved.

关键词： Unsupervised learning

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Enhanced Security Framework for Enabling Facial Recognition in Autonomous Shuttles Public Transportation During COVID-19 17th

Enhanced Security Framework for Enabling Facial Recognition ...

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17th IFIP WG 12.5 International conference on Artificial Intelligence Applications and Innovations (AIAI) / 6th 5G-PINE Workshop / AI-BIO Workshop / DAAI Workshop / DARE Workshop / EEAI Workshop / 10th MHDW Workshop

作者： Tsiktsiris, Dimitris Lalas, Antonios Dasygenis, Minas Votis, Konstantinos Tzovaras, Dimitrios Informat Technol Inst Ctr Res & Technol Hellas 6th Km Xarilaou Thermi Thessaloniki 57001 Greece Univ Western Macedonia Dept Elect & Comp Engn Kozani 50100 Greece

ISBN: (纸本)9783030791520;9783030791506;9783030791490

Autonomous Vehicles (AVs) can potentially reduce the accident risk while a human is driving. they can also improve the public transportation by connecting city centers with main mass transit systems. the development of technologies that can provide a sense of security to the passenger when the driver is missing remains a challenging task. Moreover, such technologies are forced to adopt to the new reality formed by the COVID-19 pandemic, as it has created significant restrictions to passenger mobility through public transportation. In this work, an image-based approach, supported by novel AI algorithms, is proposed as a service to increase autonomy of non-fully autonomous people such as kids, grandparents and disabled people. the proposed real-time service, can identify family members via facial characteristics and efficiently ignore face masks, while providing notifications for their condition to their supervisor relatives. the envisioned AI-supported security framework, apart from enhancing the trust to autonomous mobility, could be advantageous in other applications also related to domestic security and defense.

关键词： Autonomous vehicles Public transportation Neural networks image processing Security

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