نتایج جستجو برای: satellite networks
تعداد نتایج: 503336 فیلتر نتایج به سال:
We present a microelectrofusion method for construction of fluid-state lipid bilayer networks of high geometrical complexity up to fully connected networks with genus = 3 topology. Within networks, self-organizing branching nanotube architectures could be produced where intersections spontaneously arrange themselves into three-way junctions with an angle of 120 degrees between each nanotube. Fo...
Congestion in the Internet results in wasted bandwidth and also stands in the way of guaranteeing QoS. The effect of congestion is multiplied many fold in Satellite networks, where the resources are very expensive. Thus congestion control has a special significance in the performance of Satellite networks. In today’s Internet, congestion control is implemented mostly using some form of the de f...
This paper describes the time variant changes in satellite images using Self Organizing Feature Map (SOFM) technique associated with Artificial Neural Network. In this paper, we take a satellite image and find the time variant changes using above technique with the help of MATLAB. This paper reviews remotely sensed data analysis with neural networks. First, we present an overview of the main co...
Purpose/Objective: To develop a new recommendation studying the QoS performance for TCP transport over satellite networks including GEO, LEO, and MEO with differentiated services. Satellite network modeling and simulation results will be used for evaluations. This new recommendation will be in reference to IP over satellite matters. Background: Satellite networks play an indispensable role in p...
This issue presents the second of the two-part special topic series, ‘Cross-Layer Protocols for Satellite Communication Networks’. Cross-layer protocols for satellite networks is an emerging research area addressing the major issues of protocol design, analysis and optimization for efficient use of satellite resources and system deployment. The cross-layer design research is an interdisciplinar...
A number of satellite communication systems have been proposed using geosynchronous (GEO) satellites, medium earth orbit (MEO) and low earth orbit (LEO) constellations operating in the Ka-band and above. The next generation broadband satellite systems will use fast packet switching with onboard processing to provide full two-way services to and from earth stations. New services gaining momentum...
The digital surface model (DSM) is an important product in the field of photogrammetry and remote sensing and has variety of applications in this field. Existed techniques require more than one image for DSM extraction and in this paper it is tried to investigate and analyze the probability of DSM extraction from a single satellite image. In this regard, an algorithm based on deep convolutional...
Change detection is done with the purpose of analyzing two or more images of a region that has been obtained at different times which is Generally one of the most important applications of satellite imagery is urban development, environmental inspection, agricultural monitoring, hazard assessment, and natural disaster. The purpose of using deep learning algorithms, in particular, convolutional ...
In this paper we present a model to study the end-to-end delay performance of a satellite-ATM network. We describe a satellite-ATM network architecture. The architecture presents a trade-off between the on-board switching/processing features and the complexity of the satellite communication systems. The end-to-end delay of a connection passing through a satellite constellation consists of the t...
Using Satellite Imagery for Good: Detecting Communities in Desert and Mapping Vaccination Activities
Deep convolutional neural networks (CNNs) have outperformed existing object recognition and detection algorithms. On the other hand satellite imagery captures scenes that are diverse. This paper describes a deep learning approach that analyzes a geo referenced satellite image and efficiently detects built structures in it. A Fully Convolution Network (FCN) is trained on low resolution Google ea...
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