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Colour Palette as Support for CNN Colorization

Colour Palette as Support for CNN Colorization

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multimedia computing, networking and Applications (MCNA), International conference on

作者： Sanae BOUTARFASS Bernard BESSERER MIA Laboratory University of La Rochelle LA ROCHELLE France

ISBN: (数字)9781728183732

ISBN: (纸本)9781728183749

Colorization is the process of converting a black and white image - lot of different shades of grey - into a realistic colour image. Most of the published works uses data sets with colour images and turns these into greyscale at training stage. CNN are quite good in classification task and can easily recognize skies, trees and foliage, faces and persons, and usually colorization works well for these elements, but fails to give accurate colour to a car, mostly because if a car is highlighted in an image, it's a sport car and all sport cars are red.! Improvement is possible by using a pre-trained network for colorization and further strengthen the training process by adding a palette of relevant (salient) colours to the monochrome image. Our palette generation emphasizes salient colours aside from memorable colours (sky blue, leaf green), the latter are generally well recreated by most pre-trained CNNs devoted to colorization. When the network is finally used, the user defines some hints (i.e. small colour palette) prior to the colorization tasks. Unlike manual colorization these hints are provided once for a collection of images, making the technique suitable for movie colorization.

关键词： Image color analysis Automobiles Training Task analysis Feature extraction Faces multimedia computing

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Analytical Modelling of Content Transfer in Information Centric Networks

Analytical Modelling of Content Transfer in Information Cent...

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IEEE International conference on Computational Science and Engineering, CSE

作者： Han Xu Haozhe Wang Jia Hu Geyong Min University of Exeter Exeter UK

ISBN: (纸本)9781665416610

The proliferation of advanced information technology applications such as Virtual/Augmented Reality and ultra-high-definition (UHD) multimedia services that demand high bandwidth and ultra-low latency put tremendous pressure on the current communication networks. To meet these pressing requirements, Information-Centric Networks (ICN), a promising future Internet paradigm has been attracting much research attention. ICN deploy ubiquitous in-network caching that could not only handle large content dissemination and retrieval but also expedite the content delivery. To investigate the performance of ICN, it is important to have an analytical model that can accurately characterize the content transfer in ICN under different network and traffic conditions. In this paper, we exploit the queueing network theory to develop a new analytical model for content transfer in ICN. We derive the mathematical expressions for calculating cache miss rate and content delivery time. The accuracy of our analytical model is validated by comparing the analytical results with those obtained from simulation experiments. We also use the model to investigate the content delivery time under various network and traffic conditions.

关键词： Analytical models Scientific computing Computational modeling Information-centric networking Pressing Predictive models Mathematical models

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Evaluating QoS in SDN-Based EPC: A Comparative Analysis 15

Evaluating QoS in SDN-Based EPC: A Comparative Analysis

引用

15th IEEE International Wireless Communications and Mobile computing conference (IEEE IWCMC)

作者： Al Mtawa, Y. Memari, A. Haque, A. Lutfiyya, H. Western Univ Dept Comp Sci London ON N6A 5B7 Canada

ISBN: (纸本)9781538677476

Software Defined networking (SDN) is an emerging paradigm in networking and of high interest to the mobile network operators due to its potential benefit in improving network performance. The idea of integrating SDN in mobile network architecture, such as in LTE-evolved packet core (EPC), has already been proposed by many researchers. The SDN-based EPC network offers better Quality of Service (QoS) which is critical to the successful delivery of real-time multimedia applications in the mobile operator networks. In this paper, we provide state-of-the-art work to evaluate and analyze the QoS metrics in real-time services. We conduct a comprehensive comparison between the performance of EPC and SDN-based EPC regarding latency, jitter, and packet loss. We inject active probe packets in the networks to collect statistical data about the metrics. Various levels of workload are applied to test the robustness and stability of both EPC and SDN-based EPC designs. Our results show that SDN-based EPC significantly outperforms its legacy counterpart in all three QoS metrics. To the best of our knowledge, our study is the first comparative analysis that evaluates QoS in EPC and SDN-based EPC for real-time applications.

关键词： Quality of Service (QoS) Software Defined networking (SDN) Evolved Packet Core (EPC)

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COVID-19 Candidate Treatments, a Data Analytics Approach

COVID-19 Candidate Treatments, a Data Analytics Approach

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multimedia computing, networking and Applications (MCNA), International conference on

作者： Gerry Wolfe Ashraf Elnashar Will Schreiber Izzat Alsmadi Syracuse University Syracuse NY Texas A&M San Antonio TX

ISBN: (数字)9781728183732

ISBN: (纸本)9781728183749

COVID-19, short for “coronavirus disease 2019” has majorly affected millions of people worldwide. In the U.S. alone as of the end of this week (June 1, 2020), there have been 1,790,191 total cases, with 104,383 deaths. There have been 6,166,978 cases in the entire world, with 372,037 deaths, these are just the reported cases. Our focus in this research is in evaluating a repository of research papers to extract knowledge related to COVID-19 and possible treatments. Driven by the COVID-19 Open Research Dataset Challenge from Kaggle, we focused on a subset of that, COVID-19 Pulmonary Risks Literature Clustering. The second dataset we are using is from the Maryland Transportation Institute (MTI). The data is broken up into four categories: (1) Mobility and Social Distancing, (2) COVID and Health, (3) Economic Impact, and (4) Vulnerable Population. The data is extracted from NPR, ESRI, the COVID tracking project, CDC, and several other sources. MTI has been the source of several papers regarding mobility impact, social distancing, stay at-home orders, and non-pharmaceutical interventions.

关键词： COVID-19 Diseases Libraries Feature extraction Data models multimedia computing Dictionaries

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Radiography Classification: A Comparison between Eleven Convolutional Neural Networks

Radiography Classification: A Comparison between Eleven Conv...

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multimedia computing, networking and Applications (MCNA), International conference on

作者： Ananda Cefa Karabağ Aram Ter-Sarkisov Eduardo Alonso Constantino Carlos Reyes-Aldasoro School of Mathematics Computer Science and Engineering City University of London London UK

ISBN: (数字)9781728183732

ISBN: (纸本)9781728183749

This paper investigates the classification of normal and abnormal radiographic images. Eleven convolutional neural network architectures (GoogleNet, Vgg-19, AlexNet, SqueezeNet, ResNet-18, Inception-v3, ResNet-50, Vgg-16, ResNet-101, DenseNet-201 and Inception-ResNet-v2) were used to classify a series of x-ray images from Stanford Musculoskeletal Radiographs (MURA) dataset corresponding to the wrist images of the data base. For each architecture, the results were compared against the known labels (normal / abnormal) and then the following metrics were calculated: accuracy (labels correctly classified) and Cohen's kappa (a measure of agreement) following MURA guidelines. Numerous experiments were conducted by changing classifiers (Adam, Sgdm, RmsProp), the number of epochs, with/without data augmentation. The best results were provided by InceptionResnet-v2 (Mean accuracy = 0.723, Mean Kappa = 0.506). Interestingly, these results lower than those reported in the Leaderboard of MURA. We speculate that to improve the results from basic CNN architectures several options could be tested, for instance: pre-processing, post-processing or domain knowledge, and ensembles.

关键词： Wrist Computer architecture Training Musculoskeletal system Convolutional neural networks multimedia computing Feature extraction

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A multimedia Platform for Mexican Cultural Heritage Diffusion 11th

A Multimedia Platform for Mexican Cultural Heritage Diffusio...

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11th International conference on multimedia and Network Information Systems (MISSI)

作者： de Asis Lopez-Fuentes, Francisco Alejandro Ibanez-Ramirez, Juan Univ Autonoma Metropolitana Cuajimalpa Mexico City 04871 DF Mexico

ISBN: (纸本)9783319986784;9783319986777

New Web technologies that allow greater interaction among users have emerged in the Internet. In such a way that now it is common for users to participate actively by writing, publishing, exchanging or sharing digital content over the Internet. This fact has allowed the emergence of web communities, web services, social networking services, wikis, blogs, etc. that are developed on a specific topic. This paper presents a multimedia web platform for the creation, edition and dissemination of historical cultural contents. Security strategies are considered in the design and implementation of the interactive platform. A digital platform with this purpose is very important due to the great cultural heritage of Mexico. We evaluate the operation of our platform with cultural information related with different historic stages of Mexico such as prehispanic, colonial and independent. Our proposal seeks that the population has knowledge of cultural and historical contents in order to continuing preserve their cultural heritage.

关键词： Distributed application multimedia Internet Web 2.0

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Q-Learning Based D2D Offloading for Statistical QoS Provisioning over 5G multimedia Edge-computing Wireless Networks

Q-Learning Based D2D Offloading for Statistical QoS Provisio...

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2019 INFOCOM IEEE conference on Computer Communications Workshops, INFOCOM WKSHPS 2019

作者： Wang, Jingqing Zhang, Xi Networking and Information Systems Laboratory Department of Electrical and Computer Engineering Texas AandM University College StationTX77843 United States

ISBN: (纸本)9781728118789

With the increasing demand for the wireless multimedia services over 5G multimedia edge-computing wireless networks, the statistical quality-of-service (QoS) provisioning has been proven to be able to effectively guarantee the multimedia data transmissions over time-varying wireless channels. On the other hand, the collaborative device-to-device (D2D) based offloading scheme, where the mobile users share the popular multimedia files within a D2D communication group instead of downloading from the remote backhaul networks, has been proposed as one of the 5G promising candidate techniques to meet the statistical delaybounded QoS requirements as well as address the data explosion problem introduced by 5G multimedia edge-computing wireless networks. However, due to the dynamically changing environment and various demands for each mobile user, it is challenging to design an efficient offloading algorithm for choosing the optimal D2D offloading strategy. To overcome the aforementioned problems, in this paper we propose the machine-learning based framework for the collaborative D2D offloading scheme through repeatedly interacting with the networking environment while satisfying the statistical delay-bounded QoS constraints. In particular, we derive and analyze the collaborative D2D communication model and the interference based constraints. Under the statistical delaybounded QoS requirements, we formulate and solve the effectivecapacity optimization problem for the collaborative D2D offloading scheme by using Q-learning technique over 5G multimedia edgecomputing wireless networks. Also conducted is a set of simulations which evaluate the system performance and show that our proposed collaborative D2D offloading scheme outperforms the other existing schemes under the statistical delay-bounded QoS constraints over 5G multimedia edge-computing wireless networks. © 2019 IEEE.

关键词： Wireless networks

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Intelligent ERP Based Multi Agent Systems and Cloud computing 1st

Intelligent ERP Based Multi Agent Systems and Cloud Computin...

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1st International conference on Machine Learning for networking (MLN)

作者： Bouchemal, Nardjes Bouchemal, Naila Univ Ctr Mila Mila Algeria LIRE Lab Constantine2 Constantine Algeria Ecole Cent Elect Paris Paris France

ISBN: (纸本)9783030199456;9783030199449

The use of agents makes ERP systems more intelligent. They provide capabilities to independently interact with their surrounding environment and performing autonomous actions while cooperating with other systems Regarding the cloud computing, its use is almost obvious. It provides access to full-function applications at a rational cost without a substantial upfront for hardware and software spending. In this paper, we propose an Intelligent ERP system based on new technologies: agents and cloud computing. This combination makes ERP users (managers, customers, employees, etc.) expect data to be made available to them via the most widely used communication mobile device.

关键词： Multi agent system Intelligent ERP Cloud computing JADE-Leap

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Timeliness of Open Data in Open Government Data Portals Through Pandemic-related Data: a long data way from the publisher to the user

Timeliness of Open Data in Open Government Data Portals Thro...

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multimedia computing, networking and Applications (MCNA), International conference on

作者： Anastasija Nikiforova Faculty of Computing University of Latvia Riga Latvia

ISBN: (数字)9781728183732

ISBN: (纸本)9781728183749

The paper addresses the “timeliness” of data in open government data (OGD) portals. It is one of the primary principles of open data, which is considered to be a success factor, while at the same time it is one of the biggest barriers that can disrupt users trust in data and even the desire to use the entire open data portal. However, assessing this aspect is a very difficult task that, in most cases, becomes an impossible for open data users. There is therefore a lack of comparative studies on the timeliness of data of different national open data portals. Unfortunately, 2020 gave the opportunity to find out this. It became easy enough to compare how long is the data path from the data holder to the OGD portal by analysing the timeliness of Covid-19-related data sets in relation to the first case observed in a country. The study thus fills the gap of comparative studies by addressing 60 countries and their OGD portals concerning the timeliness of the data, providing a report on how much and what countries provide the open data as quickly as possible. It makes it possible to understand how quickly OGD portals react to emergencies by opening and updating data for their further potential reuse, which is essential in the digital data-driven world.

关键词： Portals Government COVID-19 Europe Viruses (medical) Pandemics Time-frequency analysis

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A Meter Band Rate Mechanism to Improve the Native QoS Capability of OpenFlow and OpenDaylight 2

A Meter Band Rate Mechanism to Improve the Native QoS Capabi...

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2nd International conference on Advanced Communication Technologies and networking (CommNet)

作者： Al Breiki, Mohamed Saleh Zhou, Suiping Luo, Yuan Roger Middlesex Univ Dept Comp Sci London England

ISBN: (纸本)9781538683170

The exponential growth of mobile connected devices with advanced multimedia features imposes a requirement to enhance quality of service (QoS) from heterogeneous systems and networks. In order to satisfy mission-critical multimedia QoS requirements new generation mobile networks must present content-optimized mechanisms in order to use valuable network resources efficiently and provide QoS requirements for each application. This research explores a novel solution for quality of service performance for streaming mission-critical video data in OpenFlow SDN networks. A Meter Band Rate Evaluator (MBE) Mechanism is proposed based on a new band rate description language to improve the native QoS capability of OpenFlow and OpenDaylight. Its design and development are presented and the mechanism is verified through a simulated experiment in an SDN testbed. The results revealed a significant percentage increase in QoS performance when the MBE was enabled. These findings provide support and validation for the effectiveness of the MBE to enhance the native capability of OpenFlow and OpenDaylight for efficient QoS provision.

关键词： software defined networks OpenDaylight OpenFlow quality of service meter band rate cloud computing network function virtualization heterogeneous networks 4G

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