Data-driven artificial intelligence technologies have made much progress in medical image analysis in the last decades. However, it still remains challenging due to its distinctive complexity of acquiring and annotati...
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Interest in autonomous driving (AD) and intelligent vehicles (IVs) is growing at a rapid pace due to the convenience, safety, and economic benefits. Although a number of surveys have reviewed research achievements in ...
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The main benefit of 3D display over 2D display is the obvious ability to create a more lifelike character with high depth sense. However, the limitation of human eye's visual mechanism, unartful 3D scene structure...
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The main benefit of 3D display over 2D display is the obvious ability to create a more lifelike character with high depth sense. However, the limitation of human eye's visual mechanism, unartful 3D scene structure design, or bad viewing condition always emerges poor depth perception experience or even physiological discomfort during the watching time, which is often sub-optimal for mass high-quality 3D display productions. To solve this problem, we propose a novel 3D display parallel system for depth sense optimization and it empirically guides how the light field should be re-rendered. Structurally, the parallel system consists of an artificial perception measurement system, a display evaluation model and a light field display rendering system, which includes the display calibration, scene capture, light field data processing and display. Particularly, the system can systematically analyze and model various factors affecting the depth sense which learned through the measurement system, like scene structure, objects’ speeds in 3D video and so on. And those sense factors can be personally modified or increased according to the viewer's demands or technical improvement. Moreover, the light field could be real-time re-rendered, based on some image processing technology, optical flow analysis and object segmentation (or tracking) (especially the one-shot video segmentation). Theory and algorithms are developed and experimental validation results show a superior performance.
As renewable power generation directly affects the customers' traditional electricity behavior and then offsets the power load, this paper proposes a load curve modeling method for renewable power customers based ...
As renewable power generation directly affects the customers' traditional electricity behavior and then offsets the power load, this paper proposes a load curve modeling method for renewable power customers based on the behavior analysis. Firstly, customers' active behavior is represented by the quantity of active customer households. Based on the analysis of customer behaviors, a modeling method for the quantity of active customer households is proposed based on Markov Chain Monte Carlo method. Then, with the inputs as the quantity of active customer households and time of photovoltaic power generation, an inference model based on fuzzy logic is proposed to get the quantity of customer household starting electrical appliances. By combing the average usage time of electrical appliances, load characteristics are analyzed based on usage state of electrical appliance of distributed power customers. Finally, the simulation results verify the effectiveness of the proposed method.
This article gives a capsule view of research on rough set theory and applications ongoing at universities and laboratories in China. Included in this capsule view of rough set research is a brief description of the f...
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