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Estimating depth from a single RGB image is an ill-posed and inherently ambiguous problem. State-of-the-art deep learning methods can now estimate accurate 2D depth maps, but when the maps are projected into 3D, they lack local detail and are often highly distorted. We propose a fast-to-train two-streamed CNN that predicts depth and depth gradients, which are then fused together into an accurate and...
The genetic algorithm is widely applied to all kinds of formula problems for its characteristics of simpleness, universality, strong robustness and less mathematical demands for optimization problems. However, the traditional standard genetic algorithm has a great blindness when generating the initial population and in the crossover and mutation process, which results in extremely low efficiency....
We present an improved algorithm to RRT∗ in this paper. Our algorithm tries to increase the efficiency by replacing the Initialtree() of RRT∗ with a RRT tree only contains one solution to speed up finding a feasible solution, and then applying a RRT∗_S algorithm to optimize the current solution. This RRT∗_S is similar with RRT∗ in principle, but it does not insert extra nodes into the current tree...
Frequent occurrences of meteorological disasters (MD) in recent years have revealed the deficiencies of traditional transmission network planning (TNP) methods, which fail to establish mathematical relationship between the MD and the transmission line outage rate (TLOR) when calculating the vulnerability index of transmission network. As a result, the planning schemes are usually unable to determine...
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