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ORTHOSEG: A DEEP MULTIMODAL CONVOLUTONAL NEURAL NETWORK ARCHITECTURE FOR SEMANTIC SEGMENTATION OF ORTHOIMAGERY
Deep Learning Supervised Image Segmentation Residual Networks
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2019/2/28
This paper addresses the task of semantic segmentation of orthoimagery using multimodal data e.g. optical RGB, infrared and digital surface model. We propose a deep convolutional neural network archit...
IDENTIFICATION OF SIMILARITIES AND PREDICTION OF UNKNOWN FEATURES IN AN URBAN STREET NETWORK
urban traffic traffic analysis machine learning clustering
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2018/11/9
Accurate predictions of the characteristics of urban streets in particular with respect to the typical traffic situations are crucial for numerous real world applications such as navigation, schedulin...
On Optimisation of Cluster-based Sensor Network Tracking System
WSN wireless sensor network target tracking cluster optimisation
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2016/1/23
Tracking mobile targets using low-cost Wireless Sensor Network (WSN) requires not only good tracking accuracy but also network longevity. Cluster-based tracking protocols leverage the fact that only s...
WEB-BASED NETWORK SAMPLING: EFFICIENCY AND EFFICACY OF RESPONDENT-DRIVEN SAMPLING FOR ONLINE RESEARCH
EFFICIENCY ONLINE RESEARCH
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2015/9/11
WEB-BASED NETWORK SAMPLING: EFFICIENCY AND EFFICACY OF RESPONDENT-DRIVEN SAMPLING FOR ONLINE RESEARCH.
Adjustment and transformation strategies of ItalPoS Permanent GNSS Network
GNSS Permanent Network Globk Adjustment Strategies Boucher Altamimi transformation
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2015/8/28
A private network of 133 Global Navigation Satellite Systems (GNSS) permanent sites, named ItalPoS (Italian Positioning Service) and uniformly covering the entire Italian territory, was established in...
Optimized Noisy Network Coding for Gaussian Relay Networks
Optimized Noisy Network Gaussian Relay Networks
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2015/8/17
In this paper, we provide an improved lower bound on the rate achieved by noisy network coding in arbitrary Gaussian relay networks, whose gap to the cutset upper bound depends on the network not only...
Noisy network coding unifies network coding by Ahlswede, Cai, Li, and Yeung for noiseless networks and compress–forward by Cover and El Gamal for noisy relay channels.
Noisy Network Coding
Noisy Network
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2015/8/17
A noisy network coding scheme for sending multiple sources over a general noisy network is presented. For multi-source multicast networks, the scheme naturally extends both network coding over noisele...
An interior-point method for large-scale network utility maximization
Newton the interior point networks concave utility functions disperse method dual decomposition algorithm
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2015/8/10
We describe a specialized truncated Newton primal-dual interior-point method that solves large scale network utility maximization problems, with concave utility functions, efficiently and reliably. Ou...
Dynamic network utility maximization with delivery contracts
Variation of network the matrix the flow the numerical values
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2015/8/10
We consider a multi-period variation of the network utility maximization problem that includes delivery constraints. We allow the flow utilities, link capacities and routing matrices to vary over time...
Optimizing adaptive modulation in wireless networks via multi-period network utility maximization
Wireless network control strategy the network traffic data video function
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2015/8/7
We present a crosslayer technique to find and characterize optimal control policies for wireless networks operating at different time scales at the upper layer and physical layer. The technique can al...
NETWORK CENTRALITY AND INSTITUTIONAL DESIGN: EVIDENCE FROM A LAB EXPERIMENT IN THE FIELD
Social networks Institutional design Informal contracting
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2015/7/15
While social closeness mitigates contractual incompleteness, we examine how communities
can enlist third parties to improve cooperation between socially distant pairs. Network-central members
may be...
NETWORK STRUCTURE AND THE AGGREGATION OF INFORMATION: THEORY AND EVIDENCE FROM INDONESIA
Networks Diff usion of information Targeting Development
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2015/7/15
We use unique data from 600 Indonesian communities on what individuals know about
the poverty status of others to study how network structure influences information aggregation.
We develop a m...
A Bayesian Network Approach to Control of Networked Markov Decision Processes
Decision Processes Contro
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2015/6/19
We consider the problem of finding an optimal feedback controller for a networked Markov decision process. Specifically, we consider a network of interconnected subsystems, where each subsystem evolve...
Information State for Markov Decision Processes with Network Delays
Network Delays Decision Processes
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2015/6/19
We consider a networked control system, where each subsystem evolves as a Markov decision process (MDP). Each subsystem is coupled to its neighbors via communication links over which the signals are d...