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检索条件"任意字段=16th Image Processing: Algorithms and Systems Symposium 2018"

共 650 条记录，以下是121-130 订阅

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16th International symposium on Pervasive systems, algorithms and Networks, I-SPAN 2019

16th International Symposium on Pervasive Systems, Algorithm...

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16th International symposium on Pervasive systems, algorithms and Networks, I-SPAN 2019

ISBN: (纸本)9783030301422

the proceedings contain 32 papers. the special focus in this conference is on Pervasive systems, algorithms and Networks. the topics include: Effective Ransomware Detection Using Entropy Estimation of Files for Cloud Services;modeling and Formal Verification of the Ticket-Based Handoff Authentication Protocol for Wireless Mesh Networks;TRUST: TRust Unguarded Service Terminals;nature-Inspired Protocols for Cloud Computing and Security systems;containers Scheduling Consolidation Approach for Cloud Computing;power Efficiency Containers Scheduling Approach Based on Machine Learning Technique for Cloud Computing Environment;a Clustering-Based Approach to Efficient Resource Allocation in Fog Computing;Enhanced Probability-Based Grant-Free Uplink Data Transmission in 5G mMTC;the Registration-Based Collision Avoidance Mechanism for IEEE 802.11ah;a Reinforcement Learning Based Intelligent System for the Healthcare Treatment Assistance of Patients with Disabilities;accurate and Lightweight Range-Free Localization for Wireless Sensor Networks;enhance Object Detection Capability with the Object Relation;a Simple Algorithm for Oncidium Orchid Cut Flower Grading with Deep Learning;Optimization of GPU Memory Usage for Training Deep Neural Networks;Computing image Intersection and Union Regions for Drosophila Neurons Based on Multi-core CPUs;performance Comparison of Lightweight Kubernetes in Edge Devices;Experimental Analysis of the Pixel Non Uniformity (PNU) in SEM for Digital Forensics Purposes;public WiFi Security Network Protocol Practices in Tourist Destination;AEB Control Strategy and Collision Analysis Considering the Human-Vehicle-Road Environment;Context-Awareness Enhances 5G MEC Resource Allocation;saliency Guided Data Association Measure for Multiple-Object Tracking;optimal Hybrid Path Planning Considering Dynamic and Static Characteristics of Intelligent Vehicles;improving Portfolio Performance Using Attribute Selection and Combination.

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theoretical and Experimental Evaluation of Hybrid ACO-k-means image Segmentation Algorithm for MRI images Using Drift-analysis 13

Theoretical and Experimental Evaluation of Hybrid ACO-k-mean...

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13th International symposium on Intelligent systems (INTELS)

作者： El-Khatib, S. A. Skobtsov, Y. A. Rodzin, S. I. Southern Fed Univ Nekrasovsky Per 44 Taganrog 347922 Russia St Petersburg State Univ Aerosp Instrumentat Bolshaya Morskaya Str 67 St Petersburg 190000 Russia

the hybrid Ant Colony Optimization (ACO) k-means image segmentation algorithm for MRI images segmentation is considered. the proposed algorithm and sub-system for the medical image segmentation have been implemented. the time complexity of proposed algorithm is investigated using consequences from Drift theorem. It is established that the proposed algorithm has a polynomial estimation of complexity. images from the Ossirix image dataset and real medical images were used for testing. Comparison of segmentation accuracy have been performed between proposed algorithm and competing algorithms C-means and Magic Wand. (C) 2019 the Authors. Published by Elsevier B.V.

关键词： MRI images segmentation Ant colony optimization k-means algorithm swarm intelligence drift-analysis

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Computed tomography dataset analysis for stereotaxic neurosurgery navigation 8

Computed tomography dataset analysis for stereotaxic neurosu...

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8th IEEE Int Conf on Advanced Optoelectron and Lasers (CAOL) / Sci Workshop on Data Sci in Modern Optoelectronics and Laser Engineering (DSMOLE) / 16th Sci Workshop on Measurement Uncertainty - Scientific, Normative, Appl and Methodical Aspects (UM)

作者： Avrunin, Oleg Tymkovych, Maksym Semenets, Valerii Piatykop, Volodimir Kharkiv Natl Univ Radio Elect Biomed Engn Dept Kharkiv Ukraine Kharkiv Natl Univ Radio Elect Dept Metrol & Tech Expertise Kharkiv Ukraine Kharkiv Natl Med Univ Neurosurg Dept Kharkiv Ukraine

ISBN: (纸本)9781728118147

Experience of design methods of image-guided navigation for stereotaxis neurosurgery is described. the above approach allows obtaining high accuracy to identify spatial the position of the reference stereotactic landmarks. Visualization of the contours of the third ventricle gives the ability to calculate the center of intracerebral stereotactic coordinates system. Use of the proposed techniques in the clinic allows significantly (up to 20%) to improve the effectiveness of stereotactic operations in parkinsonism. Methods for computer tomography image processing are proposed and analyzed. Further, increase accuracy stereotactic targeting functional surgery is associated with the development of machine analysis algorithms tomographic data with a view maximum recognition automation intracerebral landmarks taking into account their individual variability and allow to improve systems for surgical planning by using virtual and full-scale simulation modeling of the main stages a surgical intervention.

关键词： stereotaxis visualization image processing image-guided surgery navigation dataset.

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Upgrade of the Ball and Plate Laboratory Model 16th

Upgrade of the Ball and Plate Laboratory Model

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16th International-Federation-of-Automatic-Control (IFAC) Conference on Programmable Devices and Embedded systems PDES

作者： Brezina, Adam Tkacik, Milan Tkacik, Tomas Jadlovska, Slavka Tech Univ Kosice Fac Elect Engn & Informat Dept Cybernet & Artificial Intelligence Letna 9 Kosice 04200 Slovakia

this paper deals with the overall hardware and software upgrade of the Ball&Plate laboratory model used at the Center of Modern Control Techniques and Industrial Informatics (CMCT&II) at Department of Cybernetics and Artificial Intelligence (DCAI), FEEI, TUKE. Reasons for upgrading the model are described, along with the proposed solution. Design and construction of new control hardware for the model is presented. the paper next describes the implementation of program modules for controlling the position of the ball on the plate at level of the MicroController Unit (MCU) and the supervisor computer. Several approaches of image recognition with the purpose to obtain ball position are tested and compared. Finally, the paper presents the model-based design and verification of a PSD control algorithm for the Ball&Plate model. After the upgrade, the model can be used at the CMCTSLII for both research and teaching purposes, with the emphasis on the implementation of applications with high demands on hardware performance, where higher sampling rates of the control algorithms are required. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Cyber-physical systems Electronic design Embedded systems image processing Unstable system Computer vision

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Edge detector based on wavelet transform energy attributes 16

Edge detector based on wavelet transform energy attributes

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16th International Conference on Optical Technologies for Telecommunications

作者： Kostyukhina, G. V. Lyasheva, S. A. Shleymovich, M. P. Kazan Natl Res Tech Univ Kazan Russia

ISBN: (数字)9781510629905

ISBN: (纸本)9781510629905

the paper considers the model of representation of images using the energy characteristics of the wavelet transform. It describes an approach to the detection of edges on images based on the energy features of the wavelet transform. this approach is a modification of the Canny edge detector. It can be applied to the construction of effective information processing and control systems based on computer vision technologies.

关键词： computer vision image presentation models edge detector energy features of images

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A static hand gesture recognition for peruvian sign language using digital image processing and deep learning 4th

A static hand gesture recognition for peruvian sign language...

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4th Brazilian Technology symposium, BTSym 2018

作者： Lazo, Cristian Sanchez, Zaid del Carpio, Christian Universidad Nacional de Ingeniería Lima Peru

ISBN: (纸本)9783030160524

the work consists in recognizing the gestures of the alphabet in Peruvian sign language using techniques of digital image processing and a model of Deep Learning (CNN). image processing techniques are used for segmentation and tracking of the hand of the person making the gestures. Once the image of the segmented hand is used, a CNN classification model is used to be able to recognize the gesture. the image processing and CNN algorithms were implemented in the Python programming language. the database used was 23,000 images divided into 70% for training, 15% for testing and 15% for validation. Likewise, said data corresponds to 1000 images for each non-mobile gesture of the alphabet. the results obtained for the precision of the classifier were 99.89, 99.88 and 99.85% for the data of training, test and validation respectively. In the case of the Log Loss parameter, 0.0132, 0.0036, and 0.0107 were obtained for the training, testing and validation data, respectively. © Springer Nature Switzerland AG 2019.

关键词： Python

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OWA aggregated distance functions and their application in image segmentation 16

OWA aggregated distance functions and their application in i...

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IEEE 16th International symposium on Intelligent systems and Informatics (SISY)

作者： Nedovic, Ljubo Delic, Marija Ralevic, Neboja M. Univ Novi Sad Dept Fundamentals Sci Fac Tech Sci Novi Sad Serbia

ISBN: (纸本)9781538668412

In algorithms for image segmentation, distance functions represent a criterion based on which the pixels can be divided into groups of segments. Determination of the segmentation criterion includes several factors. the application of the aggregation operator enables the adjustment of the segmentation criteria according to the intuitively defined criterion. Depending on the characteristics of the applied aggregation operator and the distance functions as basic factors relevant for segmentation, the new distance functions with specified features are obtained. In this article one method for constructing distance functions using ordered weighted averaging aggregation operator is proposed. the application of the constructed functions is illustrated by the segmentation of the image through the "Fuzzy c-means clustering" algorithm for segmentation.

关键词： Aggregation operator distance function image segmentation metric OWA operators

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Improving Portfolio Performance Using Attribute Selection and Combination 16th

Improving Portfolio Performance Using Attribute Selection an...

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16th International symposium on Pervasive systems, algorithms and Networks, I-SPAN 2019

作者： Wang, Xiaoran Ho-Shek, James Ondusko, Dominik Frank Hsu, D. Laboratory of Informatics and Data Mining Department of Computer and Information Sciences Fordham University New YorkNY10023 United States

ISBN: (纸本)9783030301422

In portfolio management, stock selection and evaluation can be based on a variety of financial attributes over a period of time. It has been shown recently by Irukulapati et al. that long term portfolio management strategy using attribute selection and combinatorial fusion can not only achieve better results than individual attributes but also exceed the performance of the Russell 2000 index. In this paper, we propose a method to compute the attribute scoring system using weighted average by recency (AR) giving more weight to scores at the time closer to the present. We then show, by market testing, that our results perform better than that of Irukulapati et al. in a majority of cases as well as the Russell 2000. © 2019, Springer Nature Switzerland AG.

关键词： Financial data processing

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Technological line for creation and research of diffractive optical elements 16

Technological line for creation and research of diffractive ...

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16th International Conference on Optical Technologies for Telecommunications

作者： Kazanskiy, Nikolay L. Skidanov, Roman V. RAS Image Proc Syst Inst Molodogvardeyskaya 151 Samara 443001 Russia Samara Natl Res Univ Moskovskoye Shosse 34 Samara 443086 Russia

ISBN: (数字)9781510629905

ISBN: (纸本)9781510629905

We report on the creation and use of a unique object of scientific infrastructure - a technological line designed to create and study diffractive optical elements (DOEs). the technological line is a key element of the Center for Collective Use of Equipment "Diffractive Optics and Nanophotonics", created by joint efforts of scientists of Samara University and the image processing systems Institute of the Russian Academy of Sciences. the line includes both the purchased equipment and software, and unique in-house developments. the line covers all stages of DOE creation: from calculation and modeling to experimental research, including development and testing of DOE-based devices.

关键词： diffractive optics optical microrelief synthesis lithography microrelief profile control optical instrumentation hyperspectral equipment laser technology

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Scene Recognition in User Preference Prediction Based on Classification of Deep Embeddings and Object Detection 16th

Scene Recognition in User Preference Prediction Based on Cla...

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16th International symposium on Neural Networks (ISNN)

作者： Savchenko, Andrey, V Rassadin, Alexandr G. Natl Res Univ Higher Sch Econ Lab Algorithms & Technol Network Anal Nizhnii Novgorod Russia

ISBN: (纸本)9783030228088;9783030228071

In this paper we consider general scene recognition problem for analysis of user preferences based on his or her photos on mobile phone. Special attention is paid to out-of-class detections and efficient processing using MobileNet-based architectures. We propose the three stage procedure. At first, pre-trained convolutional neural network (CNN) is used extraction of input image embeddings at one of the last layers, which are used for training a classifier, e.g., support vector machine or random forest. Secondly, we fine-tune the pre-trained network on the given training set and compute the predictions (scores) at the output of the resulted CNN. Finally, we perform object detection in the input image, and the resulted sparse vector of detected objects is classified. the decision is made based on a computation of a weighted sum of the class posterior probabilities estimated by all three classifiers. Experimental results with a subset of imageNet dataset demonstrate that the proposed approach is up to 5% more accurate when compared to conventional fine-tuned models.

关键词： image recognition Scene recognition Convolutional neural network (CNN) Object detection Ensemble of classifiers Classifier fusion

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