Remote sensing of the Earth allows to receive medium information, a high spatial resolution from space vehicles, and to conduct hyperspectral measurements. This study presents a remote sensing application using time-s...
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ISBN:
(纸本)9781510651531;9781510651524
Remote sensing of the Earth allows to receive medium information, a high spatial resolution from space vehicles, and to conduct hyperspectral measurements. This study presents a remote sensing application using time-series Landsat satellite images to monitor the solid waste disposal site (WDS). The article proposes algorithms for working with spatial information, namely the transformation (convolution) of these manifolds into a one-dimensional sample. Recursive quasi-continuous sweeps are used for which the following conditions are satisfied: 1) preservation of the topological proximity of the original and expanded spaces, 2) preservation of correlations between the elements of the original and transformed spaces. An automated system is proposed for detecting and investigating waste objects based on the concept of fractal sets and convolutional neural networks. The first neural network detects WDS, the second works to localize the waste objects. This technique can become the object of further research on developing a medical-prophylactic expert system at the territorial level to detect and neutralize unauthorized waste disposal sites based on medium and high-resolution space images. As a result, the proposed method demonstrates good accuracy in detecting the solid waste disposal site on real satellite images.
In decision diagrams (DDs) methods for circuit synthesis, it is possible to directly transfer a DD for a given function f into a network realizing f by the replacement of non-terminal nodes in the DD with the correspo...
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In decision diagrams (DDs) methods for circuit synthesis, it is possible to directly transfer a DD for a given function f into a network realizing f by the replacement of non-terminal nodes in the DD with the corresponding circuit modules. The chief bottleneck of mapping a DD into a network is the inherent feature that the depth of the network produced, is equal to the number of variables in f. For this reason, it is proposed a method for small depth circuit synthesis through reachability matrices describing connections among the nodes in the DD for f. In this paper, we first generalized DD methods for circuit design to fibonacci interconnection topologies through the fibonacci decision diagrams (FibDDs). Then, we extended the small depth circuit synthesis method to FibDDs. In this way, design methods through DDs are completely transferred from Boolean to fibonacci topologies.
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