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PERCEPTUAL LOSS FOR SUPERPIXEL-LEVEL MULTISPECTRAL AND PANCHROMATIC IMAGE CLASSIFICATION

PERCEPTUAL LOSS FOR SUPERPIXEL-LEVEL MULTISPECTRAL AND PANCH...

引用

ieee International conference on Acoustics, Speech and Signal Processing

作者： Cheng Shi Chi-Man Pun Department of Computer and Information Sciences University of Macau Macau China

ISBN: (纸本)9781538646595

Convolutional neural networks (CNNs) have proven to be an effective way for deep feature extraction. However, multi-spectral and panchromatic images are susceptible to illumination unevenness and noise, and the default cross entropy loss function consider only the local information, resulting in misclassification. In this paper, we propose a novel super-pixel-level deep neural networks for multispectral and panchromatic images classification, and define a novel perceptual loss function via non-local spectral and structure similarity to suppress the interference of unbalanced light and noise. We also propose the corresponding iteration optimization algorithm in this paper. Experimental results show that the proposed method performs better than the state-of-the-art methods.

关键词： Perceptual loss function Convolutional neural networks Spectral similarity constraint Structure similarity constraint MULTISPECTRAL panchromatic image Noise local information. images Misclassification Image classification Feature extraction Neural network

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A Time Sharing Based Approach to Accommodate Similar Gain Users in NOMA for 5G networks 42

A Time Sharing Based Approach to Accommodate Similar Gain Us...

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ieee 42nd conference on local computer networks (ieee LCN)

作者： Shahab, Muhammad Basit Shin, Soo Young Kumoh Natl Inst Technol KIT Dept IT Convergence Engn WENS Lab Gumi South Korea

ISBN: (纸本)9781509065837

This paper investigates a time sharing (TS) based user pairing strategy to accommodate similar gain users in non-orthogonal multiple access (NOMA) systems, termed as TS-NOMA. A scenario is considered in which the distribution of users in a cellular area is non-uniform, such that the number of cell center users is less than cell edge users. In this case, if two user conventional NOMA (C-NOMA) pairing between cell center and cell edge users is applied, then some cell edge users remain unpaired as they are more in number. These unpaired users can be served using conventional multiple access (OMA) schemes. To accommodate these unpaired users and to efficiently utilize their spectrum, the TS-NOMA user pairing pairs a cell center user with two or more clustered (closely located) cell edge users in a TS fashion. Ergodic sum capacity of TS-NOMA is analytically derived, which is later validated through simulations. It is shown through simulations that the performance of TS-NOMA in terms of ergodic sum capacity is better than C-NOMA and OMA.

关键词： User pairing conventional non-orthogonal multiple access (C-NOMA) time sharing (TS) based NOMA (TS-NOMA) orthogonal multiple access (OMA) ergodic sum capacity (ESC)

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Discriminative Dictionary Learning with local Constraints for Face Recognition with Occlusion 4th

Discriminative Dictionary Learning with Local Constraints fo...

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4th International conference on Cloud Computing and Security (ICCCS)

作者： Zhang, Tao Yang, Zhuoqun Xu, Yaqi Yang, Bin Jia, Wenjing Jiangnan Univ Jiangsu Prov Engn Lab Pattern Recognit & Computat Wuxi Jiangsu Peoples R China Jiangnan Univ Dept Design Wuxi Jiangsu Peoples R China Univ Technol Sydney Fac Engn & Informat Technol Ultimo Australia

ISBN: (纸本)9783030000219;9783030000202

Facial occlusion, such as sunglasses, mask etc., is one important factor that affects the accuracy of face recognition. Unfortunately, faces with occlusion are quite common in the real world. In recent years, sparse coding becomes a hotspot of dealing with face recognition problem under different illuminations. The basic idea of sparse representation-based classification is a general classification scheme in which the training samples of all classes were taken as the dictionary to represent the query face image, and classified it by evaluating which class leads to the minimal reconstruction error of it. However, how to balance the shared part and class-specific part in the learned dictionary is not a trivial task. In this paper we make two contributions: (i) we present a new occlusion detection method by introducing sparse representation-based classification model;(ii) we propose a new sparse model which incorporates the representation-constrained term and the coefficients incoherence term. Experiments on benchmark face databases demonstrate the effectiveness and robustness of our method, which outperforms state-of-the-art methods.

关键词： Face recognition Occlusion detection Sparse representation

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Micro Operators for Ultra-Dense Network Deployment with Network Slicing and Spectrum Micro Licensing

Micro Operators for Ultra-Dense Network Deployment with Netw...

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ieee conference on Vehicular Technology (VTC)

作者： Marja Matinmikko-Blue Seppo Yrjoelae Matti Latva-aho Centre for Wireless Communications University of Oulu Oulu Finland Nokia Oulu Finland

5G emerges with ultra-dense deployments of small cell networks to address the location specific service demand of various vertical sectors. While the development of technical solutions for network densification is progressing, less attention has been paid to local operator models and location specific service offerings. Efficient local service delivery promoting innovation and competition calls for opening of the mobile market for new entrants to operate local radio access networks (RAN) and 3rd parties to integrate their services into the networks. This paper applies the recently proposed micro operator concept to local ultra-dense networks where different stakeholders can become micro operators and deploy their small cell RAN for tailored service delivery. We depict the resulting high-level architecture and enabling techniques focusing on network slicing and spectrum micro licensing. While network slicing is well addressed in 5G research from the mobile network operator (MNO) view for providing an end-to-end connection for 3rd parties, there is little work on how the ultra-dense small cell RAN could be operated by another stakeholder. Micro operators could offer the RAN or end-to-end network slice that comprises of network elements belonging to different stakeholders with the help of local spectrum micro licensing with quality guarantees.

关键词： computer architecture Network slicing Cloud computing Stakeholders Microprocessors 5G mobile communication

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Selection of Energy Efficient Routing Protocol for Irrigation Enabled by Wireless Sensor networks 42

Selection of Energy Efficient Routing Protocol for Irrigatio...

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ieee 42nd conference on local computer networks (ieee LCN)

作者： Abedin, Zainal Paul, Sukanta Akhter, Sharmin Siddiquee, Kazy Noor-e-Alam Hossain, Mohammad Shahadat Andersson, Karl Univ Sci & Technol Chittagong Fac Sci Engn & Technol Chittagong 1079 Bangladesh Univ Chittagong Dept Comp Sci & Engn Chittagong 4331 Bangladesh Lulea Univ Technol Pervas & Mobile Comp Lab SE-93187 Skelleftea Sweden

ISBN: (纸本)9781509065837

Wireless Sensor networks (WSNs) are playing remarkable contribution in real time decision making by actuating the surroundings of environment. As a consequence, the contemporary agriculture is now using WSNs technology for better crop production, such as irrigation scheduling based on moisture level data sensed by the sensors. Since WSNs are deployed in constraints environment, the life time of sensors is very crucial for normal operation of the networks. In this regard routing protocol is a prime factor for the prolonged life time of sensors. This research focuses the performances analysis of some clustering based routing protocols to select the best routing protocol. Four algorithms are considered, namely Low Energy Adaptive Clustering Hierarchy (LEACH), Threshold Sensitive Energy Efficient sensor Network (TEEN), Stable Election Protocol (SEP) and Energy Aware Multi Hop Multi Path (EAMMH).The simulation is carried out in Matlab framework by using the mathematical models of those algorithms in heterogeneous environment. The performance metrics which are considered are stability period, network lifetime, number of dead nodes per round, number of cluster heads (CH) per round, throughput and average residual energy of node. The experimental results illustrate that TEEN provides greater stable region and lifetime than others while SEP ensures more throughput.

关键词： Routing Protocol Life Time LEACH TEEN SEP EAMMAH Heterogeneous Stable Region Throughput

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Simple Black-Box Adversarial Attacks on Deep Neural networks 30

Simple Black-Box Adversarial Attacks on Deep Neural Networks

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30th ieee/CVF conference on computer Vision and Pattern Recognition Workshops (CVPRW)

作者： Narodytska, Nina Kasiviswanathan, Shiva VMware Res Palo Alto CA 94304 USA Samsung Res Amer Mountain View CA USA

ISBN: (纸本)9781538607336

Deep neural networks are powerful and popular learning models that achieve state-of-the-art pattern recognition performance on many computer vision, speech, and language processing tasks. However, these networks have also been shown susceptible to crafted adversarial perturbations which force misclassification of the inputs. Adversarial examples enable adversaries to subvert the expected system behavior leading to undesired consequences and could pose a security risk when these systems are deployed in the real world. In this work, we focus on deep convolutional neural networks and demonstrate that adversaries can easily craft adversarial examples even without any internal knowledge of the target network. Our attacks treat the network as an oracle (black-box) and only assume that the output of the network can be observed on the probed inputs. Our attacks utilize a novel local-search based technique to construct numerical approximation to the network gradient, which is then carefully used to construct a small set of pixels in an image to perturb. We demonstrate how this underlying idea can be adapted to achieve several strong notions of misclassification. The simplicity and effectiveness of our proposed schemes mean that they could serve as a litmus test for designing robust networks.

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

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Combating Bufferbloat in Multi-Bottleneck networks: Equilibrium, Stability, and Algorithms

Combating Bufferbloat in Multi-Bottleneck Networks: Equilibr...

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ieee Annual Joint conference: INFOCOM, ieee computer and Communications Societies

作者： Jiancheng Ye Ka-Cheong Leung Victor O.K. Li Steven H. Low Department of EEE The University of Hong Kong Hong Kong Departments of CMS & EE California Institute of Technology Pasadena CA USA

ISBN: (纸本)9781538641293

Bufferbloat is a phenomenon where router buffers are constantly being filled, resulting in high queueing delay and delay variation. Larger buffer size and more delay-sensitive applications on the Internet have made this phenomenon a pressing issue. Active queue management (AQM) algorithms, which play an important role in combating bufferbloat, have not been widely deployed due to complicated manual parameter tuning. Moreover, AQM algorithms are often designed and analyzed based on models with a single bottleneck link, rendering their performance and stability unclear in multi-bottleneck networks. In this paper, we propose a general framework to combat bufferbloat in multi-bottleneck networks. We first conduct an equilibrium analysis for a general multi-bottleneck TCP/ AQM system and develop an algorithm to compute the equilibrium point. We then decompose the system into single-bottleneck subsystems and derive sufficient conditions for the local asymptotic stability of the subsystems. Using the proposed framework, we present a case study to analyze the stability of the recently proposed Controlled Delay (CoDel) in multi-bottleneck networks and devise Self-tuning CoDel to improve the system stability and performance. Extensive simulation results show that Self-tuning CoDel effectively stabilizes queueing delay in multi-bottleneck scenarios, and thus contributes to combating bufferbloat.

关键词： Stability analysis Asymptotic stability Delays Mathematical model Nickel Heuristic algorithms Internet

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DeepLink: A Deep Learning Approach for User Identity Linkage

DeepLink: A Deep Learning Approach for User Identity Linkage

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ieee Annual Joint conference: INFOCOM, ieee computer and Communications Societies

作者： Fan Zhou Lei Liu Kunpeng Zhang Goce Trajcevski Jin Wu Ting Zhong School of Information and Software Engneering University of Electronic Science and Technology of China Robert H. Smith School of Business University of Maryland Department of Electrical and Computer Engineering Iowa State University Ames IA

ISBN: (纸本)9781538641293

The typical aim of User Identity Linkage (UIL) is to detect when users from across different social platforms are actually one and the same individual. Existing efforts to address this problem of practical relevance span from user-profile-based, through user-generated-content-based, user-behavior-based approaches to supervised or unsupervised learning frameworks, to subspace learning-based models. Most of them often require extraction of relevant features (e.g., profile, location, biography, networks, behavior, etc.) to model the user consistently across different social networks. However, these features are mainly derived based on prior knowledge and may vary for different platforms and applications. Inspired by the recent successes of deep learning in different tasks, especially in automatic feature extraction and representation, we propose a deep neural network based algorithm for UIL, called DeepLink. It is a novel end-to-end approach in a semi-supervised learning manner, without involving any hand-crafting features. Specifically, DeepLink samples the networks and learns to encode network nodes into vector representation to capture local and global network structures which, in turn, can be used to align anchor nodes through deep neural networks. A dual learning based paradigm is exploited to learn how to transfer knowledge and update the linkage using the policy gradient method. Experiments conducted on several public datasets show that DeepLink outperforms the state-of-the-art methods in terms of both linking precision and identity-match ranking.

关键词： Couplings Feature extraction Social network services Training Machine learning Task analysis Neural networks

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Parameter selection for modeling of epidemic networks

Parameter selection for modeling of epidemic networks

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ieee Symposium on Computational Intelligence and Bioinformatics and Computational Biology (CIBCB)

作者： Michael Dube Sheridan Houghten Daniel Ashlock Dept. of Computer Science Brock University St. Catharines ON Canada Dept. of Mathematics and Statistics University of Guelph Guelph ON Canada

The accurate modeling of epidemics on social contact networks is difficult due to the variation between different epidemics and the large number of parameters inherent to the problem. To reduce complexity, evolutionary computation is used to create a generative representation of the epidemic model. Previous gains from the use of local, verses global, operators are further explored to better balance exploration and exploitation of the genetic algorithm. A typical parameter study is conducted to test this new local operator and the new method of point packing is utilized as a proof of concept to perform a better search of the parameter space. All experiments from both approaches are tested against nine epidemic profiles. The point-packing driven parameter search demonstrates that the algorithm parameters interact substantially and in a non-linear fashion, and also shows that the good parameter settings are problem specific.

关键词： Evolutionary computation Diseases Computational modeling computer science Sociology Statistics Aerospace electronics

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Enhancing Security and Scalability in Software Defined LTE Core networks

Enhancing Security and Scalability in Software Defined LTE C...

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ieee International conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

作者： Ruichun Gu Xiaolong Zhang Lei Yu Junxing Zhang College of Computer Science Inner Mongolia University of Science and Technology Baotou China College of Computer Science Inner Mongolia University Hohhot China Inner Mongolia A.R. Key Laboratory of Wireless Networking and Mobile Computing Hohhot China

The rapid development of mobile networks has revolutionized the way of accessing the Internet. The exponential growth of mobile subscribers, devices and various applications frequently brings about excessive traffic in mobile networks. The demand for higher data rates, lower latency and seamless handover further drive the demand for the improved mobile network design. However, traditional methods can no longer offer cost-efficient solutions for better user quality of experience with fast time-to-market. Recent work adopts SDN in LTE core networks to meet the requirement. In these software defined LTE core networks, scalability and security become important design issues that must be considered seriously. In this paper, we propose a scalable channel security scheme for the software defined LTE core network. It applies the VxLAN for scalable tunnel establishment and MACsec for security enhancement. According to our evaluation, the proposed scheme not only enhances the security of the channel communication between different network components, but also improves the flexibility and scalability of the core network with little performance penalty. Moreover, it can also shed light on the design of the next generation cellular network.

关键词： Security Scalability Software Long Term Evolution local area networks Cloud computing Software defined networking

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