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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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Twofold Binary image Consensus for Medical Imaging Meta-Analysis 17th

Twofold Binary Image Consensus for Medical Imaging Meta-Anal...

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17th International conference on Information processing and Management of Uncertainty in Knowledge-Based systems (IPMU)

作者： Lopez-Molina, Carlos Ruiz de Gordoa, Javier Sanchez Zelaya-Huerta, Victoria De Baets, Bernard Univ Publ Navarra Dept Automat & Comp Pamplona Spain NavarraBiomed Serv Navarro Salud Osasunbidea Pamplona Spain Univ Ghent Dept Data Anal & Math Modelling KERMIT Ghent Belgium

ISBN: (纸本)9783319914763;9783319914756

In the field of medical imaging, ground truth is often gathered from groups of experts, whose outputs are generally heterogeneous. this procedure raises questions on how to compare the results obtained by automatic algorithms to multiple ground truth items. Secondarily, it raises questions on the meaning of the divergences between experts. In this work, we focus on the case of immunohistochemistry image segmentation and analysis. We propose measures to quantify the divergence in groups of ground truth images, and we observe their behaviour. these measures are based upon fusion techniques for binary images, which is a common example of non-monotone data fusion process. Our measures can be used not only in this specific field of medical imagery, but also in any task related to meta-quality evaluation for image processing, e.g. ground truth validation or expert rating.

关键词： Data fusion Twofold Consensus Ground Truth Medical imagery Immunohistochemistry (IHC) Meta-analysis

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Pattern Recognition Framework for Histological Slide Segmentation 17th

Pattern Recognition Framework for Histological Slide Segment...

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17th International conference on Computer Information systems and Industrial Management (CISIM)

作者： Jelen, Lukasz Kulus, Michal Jurek, Tomasz Wroclaw Univ Sci & Technol Dept Comp Engn Wybrzeze Wyspianskiego 27 PL-50370 Wroclaw Poland Wroclaw Med Univ Dept Human Morphol & Embryol Histol & Embryol Div Ul Chalubinskiego 6a PL-50368 Wroclaw Poland Wroclaw Med Univ Dept Forens Med Ul J Mikulicza Radeckiego 4 PL-50345 Wroclaw Poland

ISBN: (纸本)9783319999548;9783319999531

the venous system is similar in all people, but there are some individual variations. the system is well described and compared in the literature but it seems that there is a lack of comparison on the microscopic level. In this paper we present a segmentation framework for histological image segmentation that uses a clustering approach. the described framework can be used for further comparison of the venous system at the microscopic level. For that purpose we adopted a k-means and fuzzy c-means algorithms to classify image pixels to obtain vein segmentation. the presented results are promising and achieved partitioning can further be utilized for quantitative vein comparison.

关键词： Movat FCM Segmentation KNN segmentation Fuzzy c-means k-means image processing Computer aided diagnosis Pattern Recognition Histological slide

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PotholeEye -- How Can We Effectively Maintain the Pavement Distress? (demo) 19

PotholeEye -- How Can We Effectively Maintain the Pavement D...

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Proceedings of the 17th Annual International conference on Mobile systems, Applications, and Services

作者： Juyoung Park Kiyoung Im Jung Hee Lee Korea Expressway Corporation Hwaseong Republic of Korea Geolux Seoul Republic of Korea

ISBN: (纸本)9781450366618

We propose a mobile system, called PotholeEye, for automatically monitoring the surface of a roadway and providing real-time analysis of images, with the specific goal of detecting the pavement distress. PotholeEye pre-processes the images, extracts features, and classifies the distress into a variety of types, while the road manager is driving. We have tested PotholeEye on real highway involving real settings, a camera, a mini computer, a GPS receiver, and so on, and have shown how we can effectively maintain the pavement distress.

关键词： pavement distress image processing convolution neural network

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Collaborative Computation in Self-organizing Particle systems 1

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17th International conference on Unconventional Computation and Natural Computation (UCNC)

作者： Porter, Alexandra Richa, Andrea Stanford Univ Stanford CA 94305 USA Arizona State Univ Tempe AZ USA

ISBN: (数字)9783319924359

ISBN: (纸本)9783319924359;9783319924342

Many forms of programmable matter have been proposed for various tasks. We use an abstract model of self-organizing particle systems for programmable matter which could be used for a variety of applications, including smart paint and coating materials for engineering or programmable cells for medical uses. Previous research using this model has focused on shape formation and other spatial configuration problems (e.g., coating and compression). In this work we study foundational computational tasks that exceed the capabilities of the individual constant size memory of a particle, such as implementing a counter and matrix-vector multiplication. these tasks represent new ways to use these self-organizing systems, which, in conjunction with previous shape and configuration work, make the systems useful for a wider variety of tasks. they can also leverage the distributed and dynamic nature of the self-organizing system to be more efficient and adaptable than on traditional linear computing hardware. Finally, we demonstrate applications of similar types of computations with self-organizing systems to image processing, with implementations of image color transformation and edge detection algorithms.

关键词： image processing

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Identifying an Emotional State from Body Movements Using Genetic-Based algorithms 17th

Identifying an Emotional State from Body Movements Using Gen...

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17th International conference on Artificial Intelligence and Soft Computing (ICAISC)

作者： Maret, Yann Oberson, Daniel Gavrilova, Marina Univ Calgary Calgary AB Canada Sch Engn & Architecture Fribourg Fribourg Switzerland

ISBN: (纸本)9783319912530;9783319912523

Emotions may not only be perceived by humans, but could also be identified and recognized by a machine. Emotion recognition through pattern analysis can be used in expert systems, lie detectors, medical emergencies, as well as during rescue operations to quickly identify people in distress. this paper describes a system capable of recognizing emotions based on the arm movement. Features extracted from 3D skeleton using Kinect sensor are classified by five commonly used machine learning techniques: K nearest neighbors, SVM, Decision tree, Neural Network and Naive Bayes. A genetic algorithm is then invoked to find the best system parameters to achieve the higher recognition rate. the system achieved 98.96% average accuracy on the experimental dataset.

关键词： Kinect sensor Genetic algorithm Machine learning Biometric Activity recognition image processing Risk assessment

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Unsupervised Clustering Based Real-time Shot Boundary Detection for Live Broadcasting

Unsupervised Clustering Based Real-time Shot Boundary Detect...

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International conference on Computer and Communications (ICCC)

作者： Ning Su Jun Zhang Yana Zhang Guoting Zhang Communication University of China Beijing China Academy of Broadcasting Science NRTA Beijing China

ISBN: (数字)9781728147437

ISBN: (纸本)9781728147444

the development of mobile Internet greatly facilitates information communication. the mobile live broadcasting platform has made video-sharing popular. In a long live broadcast, it is necessary to generate a video summary or some pieces of news for secondary information spreading. In order to produce a video summary in real-time, shot boundary detection (SBD) of video stream is badly needed. Traditionally, shot boundaries are determined by a threshold of feature distance in adjacent frames. It is difficult to decide a threshold applied in kinds of media content with good performance. Another, researchers have proposed Support Vector Machines (SVM) to classify shot boundaries, whose model relies much on the characteristics of training data. In terms of live broadcasting, real-time signal processing is required. this paper proposes an Unsupervised Clustering based Real-time SBD method (UCR-SBD), in which consideration is given to both detection efficiency and accuracy. Experiments show that the F value of SBD reaches 97.24% and the detection speed is 17 ms per frame on average. Finally, the proposed algorithm has been successfully applied in a real-time news reporting system for the live broadcast of CUC TV station.

关键词： Feature extraction Histograms image edge detection image color analysis Clustering algorithms Streaming media Real-time systems

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Cluster storage systems gotta have HeART: improving storage efficiency by exploiting disk-reliability heterogeneity 19

Cluster storage systems gotta have HeART: improving storage ...

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Proceedings of the 17th USENIX conference on File and Storage Technologies

作者： Saurabh Kadekodi K. V. Rashmi Gregory R. Ganger Carnegie Mellon University

ISBN: (纸本)9781931971485

Large-scale cluster storage systems typically consist of a heterogeneous mix of storage devices with significantly varying failure rates. Despite such differences among devices, redundancy settings are generally configured in a one-scheme-for-all fashion. In this paper, we make a case for exploiting reliability heterogeneity to tailor redundancy settings to different device groups. We present HeART, an online tuning tool that guides selection of, and transitions between redundancy settings for long-term data reliability, based on observed reliability properties of each disk group. By processing disk failure data over time, HeART identifies the boundaries and steady-state failure rate for each deployed disk group (e.g., by make/model). Using this information, HeART suggests the most space-efficient redundancy option allowed that will achieve the specified target data reliability. Analysis of longitudinal failure data for a large production storage cluster shows the robustness of HeART's failure-rate determination algorithms. the same analysis shows that a storage system guided by HeART could provide target data reliability levels with fewer disks than one-scheme-for-all approaches: 11-16% fewer compared to erasure codes like 10-of-14 or 6-of-9 and 33% fewer compared to 3-way replication.

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Stochastic Model on Low Resolution Characters and the Feature of Topological Invariant 17

Stochastic Model on Low Resolution Characters and the Featur...

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Joint 17th World Congress of International-Fuzzy-systems-Association / 9th International conference on Soft Computing and Intelligent systems (IFSA-SCIS)

作者： Matsuda, Takeshi Univ Nagasaki Dept Informat Secur 1-1-1 Manabino Nagoya Nagasaki 8512195 Japan

images data may contain low resolution characters, and it is not easy to estimate the given low resolution characters. this paper proposed the stochastic model of the low resolution characters and considered the topol... 详细信息

ISBN: (纸本)9781509049172

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks Signal processing algorithms

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An Iterative Algorithm for image Inpainting Using Aggregation Functions 17

An Iterative Algorithm for Image Inpainting Using Aggregatio...

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Joint 17th World Congress of International-Fuzzy-systems-Association / 9th International conference on Soft Computing and Intelligent systems (IFSA-SCIS)

作者： Gonzalez-Hidalgo, Manuel Massanet, Sebastia Mir, Amau Ruiz-Aguilera, Daniel Univ Balearic Isl SCOPIA Res Grp Dept Math & Comp Sci Cira ValldemossaKm 7-5 E-07122 Palma De Mallorca Balearic Island Spain

ISBN: (纸本)9781509049172

image inpainting is a prolific line of research due to its applications in restoration of missing or damaged areas of the image. In this paper, a novel iterative algorithm for image inpainting based on aggregation functions and penalty-based functions is presented. the algorithm combines diffusion-based and patch-based techniques. In each iteration of the algorithm, the level of consensus among the known pixels in a neighbourhood of each pixel is computed. If a minimum value of consensus is reached, the pixel is recovered by means of an aggregation of the known pixels of the neighbourhood through aggregation functions and penalty-based functions. Otherwise, a non-local search of similar patches is performed and then a similar aggregation but now of the centre pixels of those patches more similar to the region we must recover is carried out. Experiments on synthetic and natural images show the potential of this algorithm both from the qualitative and the quantitative points of view in comparison to other classical inpainting algorithms.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks Signal processing algorithms

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Modern Methods of image processing in Safety-Critical Applications within Intelligent Transportation System 1

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17th International conference on Transport systems Telematics (TST)

作者： Bubenikova, Emilia Franekova, Maria Kanalikova, Alzbeta Univ Zilina Fac Elect Engn Univ 8215-1 Zilina 01026 Slovakia

ISBN: (数字)9783319662510

ISBN: (纸本)9783319662510;9783319662503

Modern collision avoidance systems implemented into the Intelligent Transportation systems work on the base of the image information analysis. For the control of unintentional departure from the lane, the vehicles in Cooperative-intelligent Transportation systems use surveillance systems-Lane Departure Warning. A very important parameter of these systems is the reliability of the method of digital image information processing, which depends on the choice of the optimum algorithm for the detection of road markings in different light conditions. the parameters of image processing algorithms should be set on the base of software simulation with real collected traffic data. the contribution is focused on finding and testing effective methods of digital image processing algorithms to monitoring the crossing of lane with a focus on reliability evaluation.

关键词： Cooperative-intelligent transportation system Advanced driver assistance system Lane departure warning system image processing Detection algorithms Reliability

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