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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151-160 订阅

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An Evaluation on Effectiveness of Deep Learning in Detecting Small Object Within a Large image 1

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17th International conference on Biomedical Engineering, ICBME 2019

作者： Hassan, Nazirah Ming, Kong Wai Wah, Choo Keng School of Engineering Nanyang Polytechnic Nanyang Singapore

ISBN: (数字)9783030620455

ISBN: (纸本)9783030620448

Multiple Deep Learning (DL) algorithms have been developed recently and are shown to be achieving very high accuracy in object detection. However, challenges have been reported in detecting small objects within a large image (e.g. > 2000 by 2000 in resolution). Various methods have been proposed using different detection algorithms in order to detect small objects. However, these approaches require high computational resources and are not suitable for edge computing devices that are used for practical applications such as pedestrian traffic light detection. We explored two different methods of detection to evaluate which method is best at detecting small objects. the first method is a two—part procedure with the first step being image processing and the second step, a R-CNN based detection using Edge Boxes algorithm for the extraction of region proposals. the second method is solely Faster R-CNN Object Detection with Instance Segmentation, termed as Mask R-CNN. A total of 4000 streets images of Singapore with pedestrian traffic lights were used as training data. the dimensions of the images range from 1200 by 900 to 4000 by 3000. the small object to be detected is the green or red man within pedestrian traffic lights. We evaluated these methods based on training time required, detection time, accuracy as well as suitability for deployment in edge computing devices. From the results, it is shown that the HSV + R-CNN approach is preferred as it achieves an accuracy of 95.5% and can be deployed in edge devices. © 2020, Springer Nature Switzerland AG.

关键词： Object detection

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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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Can Masses of Non-Experts Train Highly Accurate image Classifiers? A Crowdsourcing Approach to Instrument Segmentation in Laparoscopic images

Can Masses of Non-Experts Train Highly Accurate Image Classi...

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17th International conference on Medical image Computing and Computer-Assisted Intervention (MICCAI)

作者： Maier-Hein, Lena Mersmann, Sven Kondermann, Daniel Bodenstedt, Sebastian Sanchez, Alexandro Stock, Christian Kenngott, Hannes Gotz Eisenmann, Mathias Speidel, Stefanie German Canc Res Ctr Comp Assisted Intervent Heidelberg Germany Heidelberg Univ Heidelberg Collaboratory Image Proc Heidelberg Germany Karlsruhe Inst Technol Inst Anthropomat & Robot D-76021 Karlsruhe Germany Heidelberg Univ Inst Med Biometry & Informat D-69115 Heidelberg Germany Heidelberg Univ Dept Gen Visceral & Transplantat Surg D-69115 Heidelberg Germany

ISBN: (纸本)9783319104706;9783319104690

Machine learning algorithms are gaining increasing interest in the context of computer-assisted interventions. One of the bottlenecks so far, however, has been the availability of training data, typically generated by medical experts with very limited resources. Crowdsourcing is a new trend that is based on outsourcing cognitive tasks to many anonymous untrained individuals from an online community. In this work, we investigate the potential of crowdsourcing for segmenting medical instruments in endoscopic image data. Our study suggests that (1) segmentations computed from annotations of multiple anonymous non-experts are comparable to those made by medical experts and (2) training data generated by the crowd is of the same quality as that annotated by medical experts. Given the speed of annotation, scalability and low costs, this implies that the scientific community might no longer need to rely on experts to generate reference or training data for certain applications. To trigger further research in endoscopic image processing, the data used in this study will be made publicly available.

关键词： Learning systems

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processing of the image from infrared focal plane array using FPGA-based system

Processing of the image from infrared focal plane array usin...

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International conference on Mixed Design of Integrated Circuits and systems (MIXDES)

作者： Tomasz Sosnowski Grzegorz Bieszczad Mariusz Kastek Henryk Madura Institute of Optoelectronics Military University of Technology Warsaw Poland

the paper presents the image processing and analysis system for a thermal camera. Presented device controls the microbolometer FPA, performs non-uniformity correction and bad pixel mapping and controls the process of displaying the thermal image. the system was designed in such a way, that signal processing algorithms, needed for specific tasks, can be implemented in it without hardware modifications. It was achieved by the application of a FPGA device and microprocessor unit, which both can be re-programmed inside the system.

关键词： Arrays image processing Pixel Cameras Detectors Field programmable gate arrays Converters

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Gpu-based parallel algorithm for solving multiphase, multicomponent fluid filtration problem 17

Gpu-based parallel algorithm for solving multiphase, multico...

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17th European conference on the Mathematics of Oil Recovery, ECMOR 2020

作者： Imankulov, T. Akhmed-Zaki, D. Daribayev, B. Turar, O. Al Farabi Kazakh National University

ISBN: (纸本)9789462823426

Hydrodynamic modeling of oil reservoir processes is one of the complex problems of fluid mechanics, since underground reservoir processes can be very complex. It is necessary to take into account phase transitions, chemical transformations, temperature effects, and etc. When simulating multiphase, multicomponent liquid filtration, the properties of the phase can vary depending on the composition of temperature and pressure. the oil phase consists of hydrocarbon components that range from the lightest (methane) to the heaviest (bitumen). You can simulate the process of multicomponent filtration, knowing the physical parameters of the pseudo-components (molecular weight, critical pressure, critical temperature, compressibility, density, viscosity, thermal conductivity and specific heat). Parallel algorithms implemented on graphic processors (GPUs) than on traditional processors (CPUs) are excellently suited to speed up such demanding tasks. In various fields of research, there have been many successful implementations on the GPU, such as medical image analysis and computational fluid dynamics. the GPU achieves high performance by executing more than a thousand threads at the same time, and each of them processes different data sets. the purpose of this paper is to implement the parallel algorithm on modern graphic processors (GPUs) for numerically solving a multiphase multicomponent fluid filtration problem in porous media, taking into account the number of phases and components. For the numerical solution of the problem, the alternating direction implicit method (ADI) was chosen. ADI is a finite difference numerical method for solving parabolic, hyperbolic and elliptic equations, and it is widely used in the fields of science and technology. In the ADI method, each numerical step is divided into several sub-steps, depending on the spatial dimension of the problem, and systems of linear equations are solved implicitly in one direction, with an explicit scheme in the o

关键词： Graphics processing unit

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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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Small plot identification from video streams for high-throughput phenotyping of large breeding populations with unmanned aerial systems 4

Small plot identification from video streams for high-throug...

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conference on Autonomous Air and Ground Sensing systems for Agricultural Optimization and Phenotyping IV held at SPIE Defense + Commercial Sensing conference

作者： Wang, Xu Amos, Cameron Lucas, Mark Williams, Grant Poland, Jesse Kansas State Univ Dept Plant Pathol 1712 Claflin Rd4024 Throckmorton PSC Manhattan KS 66506 USA Kansas State Univ Dept Biol & Agr Engn 1016 Seaton Hall920 N 17th St Manhattan KS 66506 USA Kansas State Univ Dept Aviat Technol Polytech Campus2310 Centennial Rd Salina KS 67401 USA

ISBN: (数字)9781510626829

ISBN: (纸本)9781510626829

In breeding and genetics programs, thousands of small plots in the size of a few square meters each having a unique genetic entry, are used to evaluate huge numbers of candidates and large mapping populations. Low-altitude remote sensing with unmanned aerial systems (UAS) can generate high geospatial resolution measurements of plants and enable high temporal resolution measurements through multiple crop growth stages. However, to identify individual plot from aerial images robustly and automatically becomes a key challenge in high throughput phenotyping (HTP) using UAS. In this case study, we captured super high-resolution video clips of wheat canopies by a UAS at low altitude. We proposed an image processing pipeline for identifying individual plot from video frames. Preliminary results indicate the methods can highly accelerate the process of linking genotypes to individual plot images and can be fully automated. this research provides a proof-of-concept and has broad implications of novel phenomics application of UAS that is scalable to tens-of-thousands of plots in crop breeding and genetic studies.

关键词： high-throughput phenotyping unmanned aerial system image processing wheat breeding

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Analysis of Decision Tree and Random Forest algorithms for Nutrient Deficiency Classification in Citrus Leaves through image processing

Analysis of Decision Tree and Random Forest Algorithms for N...

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International conference on Telecommunication systems, Services, and Applications (TSSA)

作者： Lia Kamelia Rin Rin Nurmalasari Electrical Engineering Department UIN Sunan Gunung Djati Bandung Bandung Indonesia

the research presents a hybrid approach to identify and categorise nutritional deficiency syndrome in citrus leaves using image processing and machine learning. the method includes processing images, segmenting images and extracting color-texture information. the Decision Tree and the Random Forest algorithms use various statistical measures for classification, including mean, skewness, variance, entropy, maximum probability, angular second moment, contrast, correlation, dissimilarity, energy, and homogeneity. the test results show a range of performance levels, with an accuracy of 80.28% being attained by utilising an 80:20 data ratio in the Decision Tree approach. the Random Forest method’s highest accuracy, 91.25%, was reached using an 80:20 ratio. In conclusion, the accuracy of the Random Forest approach regularly beats that of the Decision Tree method.

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Evolutionary-based image encryption with dna coding and chaotic systems 1

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17th International conference on Web Information systems and Applications, WISA 2020

作者： Qin, Shiyue Tan, Zhenhua Zhang, Bin Zhou, Fucai School of Computer Science and Engineering Northeastern University Shenyang China Software College Northeastern University Shenyang China

ISBN: (数字)9783030600297

ISBN: (纸本)9783030600280

In order to obtain encrypted image with optimal correlation coefficient, we propose a new evolutionary-based image encryption scheme in this paper, based on DNA coding, chaotic systems, and a genetic algorithm (GA). Firstly, the DNA encoding operation is performed over the original plain image. then logistic mapping and hyper-chaotic systems are used to create the number of encrypted images over the DNA matrices. We fix these encrypted images as the initial population for the GA, and the GA is applied to them to determine the best one based on the fitness function. the correlation coefficient is used to define the fitness function in this paper. Finally, after the evolution, the encrypted image with the lowest correlation coefficient will be obtained as the final result. the novelty of this research is in using the logistic map over the DNA matrix of the original image directly, which will make the initial group of encrypted images more secure and with lower initial fitness for the GA. therefore, the scheme will achieve high fitness in fewer iterations and retain the efficiency of the encryption. Experimental results confirm that the proposed scheme not only has a good encryption effect, but also has the ability of resisting statistical analysis attacks, brute force attacks, and differential attacks. © Springer Nature Switzerland AG 2020.

关键词： Genetic algorithms

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Natural Language processing and Deep Learning for Blended Learning as an Aspect of Computational Linguistics 17th

Natural Language Processing and Deep Learning for Blended Le...

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17th Annual conference of the International-Association-of-Online-Engineering (IAOE) and the Global-Online-Laboratory-Consortium (GOLC) on Remote Engineering and Virtual Instrumentation (REV) - Cross Reality and Data Science in Engineering

作者： Pikhart, Marcel Univ Hradec Kralove Fac Informat & Management Hradec Kralove Czech Republic

ISBN: (纸本)9783030525750;9783030525743

Machine learning has been used for several years already in information science to create algorithms which enable computers to solve problems without giving them particular tasks and instructions to perform these tasks. this paper attempts to concentrate on possibilities of this AI (artificial intelligence) subfield inasmuch it could prove helpful for blended learning. It brings possible questions which are connected to e-learning, blended learning and machine learning and its utilization in university courses. It also brings several questions of computational linguistics which could prove extremely helpful in blended learning processes in which it could bring big data analysis. these phenomena are relatively new, therefore, neglected by blended learning scholars, thus this paper brings these new ideas together and wants to present new ideas and concepts which will be utilized in blended learning area. It also suggests new approach to blended learning, coined by the term blended learning 2.0, which implements modern approaches such as computational linguistics and corpus linguistics into the utilization of e-platforms in the educational process.

关键词： Blended learning E-learning Computational linguistics Corpus linguistics Natural language processing Deep learning

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