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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141-150 订阅

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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 ...

引用

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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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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A REVIEW OF thE APPLICATION OF TECHNOLOGY ACCEPTANCE MODELS IN thE HEALthCARE 18

A REVIEW OF THE APPLICATION OF TECHNOLOGY ACCEPTANCE MODELS ...

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18th International conference on Interfaces and Human Computer Interaction 2024, IHCI 2024, the 17th International conference on Game and Entertainment Technologies 2024, GET 2024 and the 18th International conference on Computer Graphics, Visualization, Computer Vision and image processing 2024, CGVCVIP 2024, Part of the 18th Multi conference on Computer Science and Information systems 2024, MCCSIS 2024

作者： Eskandari, Sadjad Valente, Juan P. Department of Languages Information Systems and Software Engineering Universidad Politécnica de Madrid Madrid28660 Spain

ISBN: (纸本)9789898704580

In the present paper, a comprehensive review was performed on the application of technology acceptance models (TAM) in the healthcare sector. the important post-2019 published papers were searched and extracted by the Google Scholar search engine and important papers were taken into consideration for further analysis related to the use of recently utilized models on the final results of TAM based on different case studies. Although TAM has shown to have an outstanding role in predicting clinician acceptance and health information technology (IT) usage, there is still a need for improvement in cases of standardization, further relationship testing, better data reporting, and the exploration of new variables. In this regard, one can prioritize identifying clinicians' specific beliefs about health IT, enhancing the applicability of TAM in healthcare by evaluating contextual factors, barriers, facilitators, and social norms impacting IT adoption. In addition, based on the classification of recent studies into general variables and results, usefulness, ease of use, trust, and privacy concerns were determined as important factors in patients' acceptance of technology in healthcare services, and related recommendations were provided in this work. TAM-based models offer valuable insights into the adoption and acceptance of healthcare technologies and researchers and healthcare organizations should be mindful of their limitations and consider future research directions to enhance their applicability in an ever-evolving healthcare landscape. © 2024 Interfaces and Human Computer Interaction. All Rights Reserved.

关键词： Electronic health record

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Automated Summary Scoring with ReaderBench 17th

Automated Summary Scoring with ReaderBench

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17th International conference on Intelligent Tutoring systems (ITS)

作者： Botarleanu, Robert-Mihai Dascalu, Mihai Allen, Laura K. Crossley, Scott Andrew McNamara, Danielle S. Univ Politehn Bucuresti 313 Splaiul Independentei Bucharest 060042 Romania Acad Romanian Scientists Str Ilfov 3 Bucharest 050044 Romania Univ New Hampshire Durham NH 03824 USA Georgia State Univ Dept Appl Linguist ESL Atlanta GA 30303 USA Arizona State Univ Dept Psychol POB 871104 Tempe AZ 85287 USA

ISBN: (纸本)9783030804213;9783030804206

Text summarization is an effective reading comprehension strategy. However, summary evaluation is complex and must account for various factors including the summary and the reference text. this study examines a corpus of approximately 3,000 summaries based on 87 reference texts, with each summary being manually scored on a 4-point Likert scale. Machine learning models lever-aging Natural Language processing (NLP) techniques were trained to predict the extent to which summaries capture the main idea of the target text. the NLP models combined both domain and language independent textual complexity indices from the ReaderBench framework, as well as state-of-the-art language models and deep learning architectures to provide semantic contextualization. the models achieve low errors - normalized MAE ranging from 0.13-0.17 with corresponding R-2 values of up to 0.46. Our approach consistently outperforms baselines that use TF-IDF vectors and linear models, as well as Transfomer-based regression using BERT. these results indicate that NLP algorithms that combine linguistic and semantic indices are accurate and robust, while ensuring generalizability to a wide array of topics.

关键词： Natural language processing Text summarization Automated scoring

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the study of elastic streaming processing of multidimensional optical signals in a distributed computing environment

The study of elastic streaming processing of multidimensiona...

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17th International Scientific and Technical conference on Optical Technologies for Telecommuncations

作者： Popov, Sergey B. Protsenko, Vladimir, I RAS Image Proc Syst Inst Branch FSRC Crystallog & Photon 151 Molodogvardeyskaya St Samara 443001 Russia Samara Natl Res Univ 34 Moskovskoye Shosse Samara 443086 Russia

ISBN: (纸本)9781510638402;9781510638396

Current trends in increasing the intelligence level of software systems for analyzing data flows under the constraints of processing time require the study of new technologies that take advantage of a distributed computing environment. In this paper, we implement a technology for distributed streaming processing of multidimensional optical signals based on the Apache Flink framework. the technology is studied on the task of transport video surveillance tracking unique objects captured by a system of geographically dispersed video cameras. We study the ability of proposed solution scale the processing depending on the amount of resources in the cloud, the quantity and quality of optical signals. the characteristics of processing processes of a set of frames of varying complexity on a computing cluster are investigated. NVIDIA AI City Challenge is used as test data sets.

关键词： distributed streaming processing computing cluster cloud computing elasticity processing Apache Flink framework video surveillance tracking 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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Foveated image processing for Faster Object Detection and Recognition in Embedded systems Using Deep Convolutional Neural Networks 8th

Foveated Image Processing for Faster Object Detection and Re...

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8th International conference on Biomimetic and Biohybrid systems

作者： Jaramillo-Avila, Uziel Anderson, Sean R. Univ Sheffield Dept Automat Control & Syst Engn Sheffield S1 3JD S Yorkshire England

ISBN: (纸本)9783030247409;9783030247416

Object detection and recognition algorithms using deep convolutional neural networks (CNNs) tend to be computationally intensive to implement. this presents a particular challenge for embedded systems, such as mobile robots, where the computational resources tend to be far less than for workstations. As an alternative to standard, uniformly sampled images, we propose the use of foveated image sampling here to reduce the size of images, which are faster to process in a CNN due to the reduced number of convolution operations. We evaluate object detection and recognition on the Microsoft COCO database, using foveated image sampling at different image sizes, ranging from 416x416 to 96x96 pixels, on an embedded GPU - an NVIDIA Jetson TX2 with 256 CUDA cores. the results show that it is possible to achieve a 4x speed-up in frame rates, from 3.59 FPS to 15.24 FPS, using 416 x 416 and 128 x 128 pixel images respectively. For foveated sampling, this image size reduction led to just a small decrease in recall performance in the foveal region, to 92.0% of the baseline performance with full-sized images, compared to a significant decrease to 50.1% of baseline recall performance in uniformly sampled images, demonstrating the advantage of foveated sampling.

关键词： Pixels

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A Design Methodology for Hardware Acceleration of Adaptive Filter algorithms in image processing

A Design Methodology for Hardware Acceleration of Adaptive F...

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International conference on Application Specific systems (ASAP), Architectures and Processors

作者： Hritam Dutta Frank Hannig Jurgen Teich Benno Heigl Heinz Hornegger Department of Computer Science 12 University of Erlangen Nuremberg Nuremberg Germany Medical Solutions AX Siemens AG Communications Forchheim Germany

Massively parallel processor array architectures can be used as hardware accelerators for a plenty of dataflow dominant applications. Bilateral filtering is an example of a state-of-the-art algorithm in medical imaging, which falls in the class of 2D adaptive filter algorithms. In this paper, we propose a semi-automatic mapping methodology for the generation of hardware accelerators for such a generic class of adaptive filtering applications in image processing. the final architecture deliver similar synthesis results as a hand-tuned design.

关键词： Design methodology Hardware Acceleration Adaptive filters image processing Signal processing algorithms Biomedical imaging Field programmable gate arrays Medical diagnostic imaging Application software

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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)9783030293901

ISBN: (纸本)9783030293895

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.;Part I: accessibility design principles; assistive technology for cognition and neurodevelopment disorders; assistive technology for mobility and rehabilitation; assistive technology for visually impaired; co-design and design methods; crowdsourcing and collaborative work; cyber security and e-voting systems; design methods; design principles for safety/critical systems.

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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Adaptive algorithm of conforming image matching 5

Adaptive algorithm of conforming image matching

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Data Science Session at the 5th International conference on Information Technology and Nanotechnology, DS-ITNT 2019

作者： Fursov, V.A. Goshin, Ye.V. Pugachev, K.G. Samara National Research University Moskovskoe Shosse 34 Samara443086 Russia Image Processing Systems Institute of RAS Branch of the FSRC Crystallography and Photonics RAS Molodogvardejskaya street 151 Samara443001 Russia

this paper presents an adaptive algorithm of conforming image matching based on the principle of conformity. the algorithm consists of several main stages. At the first stage, we find the corresponding points using a minimum value of conformity as the measure of points’ similarity. We define a conformity function as the sum of all possible combinations of squared differences of pixel intensity values on the fragments that are matched. then, we perform an adaptive procedure of errors correction considering an intensity gradient distribution. An important feature of the algorithm is the finding of error points using a criterion of maximum value of samples’ conformity for every fragment of the disparity map. the results of experiments on the "Teddy" test images are shown. © 2019 CEUR Workshop Proceedings.

关键词： Adaptive algorithms

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