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Most of the recent successful methods in accurate object detection and localization used some variants of R-CNN style two stage Convolutional Neural Networks (CNN) where plausible regions were proposed in the first stage then followed by a second stage for decision refinement. Despite the simplicity of training and the efficiency in deployment, the single stage detection methods have not been as competitive...
Proximity detection is one of the critical components in Location-based Social Networks (LBSNS), which has attracted much attention recently. With the advent of LBSNS, more and more users' location information will be collected by the service providers. However, with a potentially untrusted server, such a proximity detection service may threaten the privacy of users. In this paper, aiming at achieving...
This paper presents a design scheme of portable AUV remote control device based on MOOS-IvP architecture. The remote control device takes the raspberry pi microcomputer as the main controller. The handle of the game is the key module. It communicates with AUV through the wireless bridge. Lithium battery supply power through the sub voltage module. The software use the Ubuntu operating system based...
Cloud services decouple cloud applications from IT infrastructure in cloud environment. On demand resources provisioning pattern makes high efficient resource utility and application dynamic scaling possible. Hence Cloud data center could provide infrastructure capabilities in a more energy efficient way. However, there exists a tradeoff between energy efficiency and application service level objectives...
This paper strives to review the contribution of systems theory to enterprise architecture and integration, make a summary of methods or tools at systems level and probe into some crucial concepts and thinking of systems theory applied in the enterprise integration activities. As the summary to this paper, some new prospects in enterprise architecture and integration are presented to tackle the increasing...
This paper deals with the behavior control strategy of autonomous robots. Since conditioned reflex and emotions make living things intelligent to adapt to different environments, they are combined with each other in the presented strategy to endow the robot with the ability of adapting to various conditions. The associative memory is also used to enhance the learning efficiency. Simulation results...
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