In this paper, we proposed a medical image fusion algorithm based on sparse representation and guided filtering. One of attractive features in the algorithm is that it can preserve the structural information of struct...
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In recent year, tremendous strides have been made in face detection thanks to deep learning. However, most published face detectors deteriorate dramatically as the faces become smaller. In this paper, we present the S...
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In this paper, we proposed a medical image fusion algorithm based on sparse representation and guided filtering. One of attractive features in the algorithm is that it can preserve the structural information of struct...
In this paper, we proposed a medical image fusion algorithm based on sparse representation and guided filtering. One of attractive features in the algorithm is that it can preserve the structural information of structural image and color information of functional image. We use a sparse representation in low frequency, initialize the dictionary by using DCT transform, and train the dictionary with each input source image as a training example. It not only ensures time complexity, but also ensures that the low-frequency fusion rules are adaptive. At high frequencies, we use the method of guided filtering to extract structural information from high-frequency images, and use the injection method to fuse high-frequency sub-bands to ensure the validity and richness of structural information. Experimental results show that the proposed fusion algorithm is superior to comparative algorithms in terms of subjective and objective evaluation methods.
Classifying performance evaluation is one of open problems in data mining and machine learning fields. We note that nearly all the existing evaluation measures ignore the predicted probabilities which are greatly sign...
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Glacier is a sensitive indicator of the climate change, and also closely related to human beings. RS and GIS supply effective means to research the change of glacier. Those are important methods for compensating the s...
Glacier is a sensitive indicator of the climate change, and also closely related to human beings. RS and GIS supply effective means to research the change of glacier. Those are important methods for compensating the shortage of previous ones. Small watershed is the basic unit of water circulation. Thus, the more reliable conclusion, which is the response of lake to glacier, will be obtained by the small watershed. In this paper, dividing the watershed into the smaller one, the Akesu River-Kaidu River small watershed was chosen as study area. Based on RS and GIS, under the climate change from cold-dry to warm-wet since 1977, 2000 and 2007, the variety of glacier was shown as decreasing firstly and then increasing a little. Meanwhile, the variety of lake was presented as increasing firstly and then decreasing greatly. However, the change tendency of glacier and lake was decreased. The decreased areas were 823.3 km2 and 239.5km2 separately. According to the spatial bivariate auto-correlation analysis map, the negative correlation between glacier and lake was more distinct. In Tianshan Mountain, owing to the change mainly influenced by elevation, glacier was decreased and lake was increased. In Bosten Lake, glacier was increased and lake was decreased due to the change mainly affected by climate.
The three-dimensional structure of a biomolecule rather than its one-dimensionM sequence determines its biological function. At present, the most accurate structures are derived from experimental data measured mainly ...
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The three-dimensional structure of a biomolecule rather than its one-dimensionM sequence determines its biological function. At present, the most accurate structures are derived from experimental data measured mainly by two techniques： X-ray crystallog- raphy and nuclear magnetic resonance （NMR） spec- troscopy. Because neither X-ray crystallography nor NMR spectroscopy could directly measure the positions of atoms in a biomolecule, algorithms must be designed to compute atom coordinates from the data. One salient feature of most NMR structure computation algorithms is their reliance on stochastic search to find the lowest energy conformations that satisfy the experimentally- derived geometric restraints. However, neither the cor- rectness of the stochastic search has been established nor the errors in the output structures could be quantified. Though there exist exact algorithms to compute struc- tures from angular restraints, similar algorithms that use distance restraints remain to be developed. An important application of structures is rational drug design where protein-ligand docking plays a crit- ical role. In fact, various docking programs that place a compound into the binding site of a target protein have been used routinely by medicinal chemists for both lead identification and optimization. Unfortunately, de- spite ongoing methodological advances and some success stories, the performance of current docking algorithms is still data-dependent. These algorithms formulate the docking problem as a match of two sets of feature points. Both the selection of feature points and the search for the best poses with the minimum scores are accomplished through some stochastic search methods. Both the un- certainty in the scoring function and the limited sam- pling space attained by the stochastic search contribute to their failures. Recently, we have developed two novel docking algorithms： a data-driven docking algorithm and a general docking algorithm that does not re
In this paper, the subject of discussion is the uncertainties of Ant Colony Algorithm(ACA). In order to find application and popularize the ACA, we try to find some disciplinarians which can eliminate the impact of un...
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