J. Digne, Similarity based filtering of point clouds, in: IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPRW, Providence, RI, 2012, pp. 73-79.Digne, J.: Similarity based
With continuous research, the theory of cloud modelling has become general and complete. Subsequently, similarity algorithms for cloud modelling have gradually become an essential part of cloud modelling theory research and have important applications in data mining [14], collaborative filtering for ...
In this paper, we propose a new filtering technique that decreases the number of comparisons between the query set and the search set to find highly similar documents. The proposed filtering technique utilizes Z-order prefix, based on the cosine similarity measure, in which only the most ...
The object fingerprint is based on an analysis of the one or more basic blocks. Thereafter, the object fingerprint is generated based on an analysis of the one or more basic blocks. Lastly, the object fingerprint is compared to one or more malware family fingerprints to determine if the ...
A non-local denoising (NLD) algorithm for point-sampled surfaces (PSSs) is presented based on similarities, including geometry intensity and features of sample points. By using the trilateral filtering operator, the differential signal of each sample point is determined and called "geometry intensity...
Digital Surface Models (DSM) were generated, performing the automatic filtering procedure for the dense cloud of points generation. The densification of the point cloud was performed based on the original scale of the image. The density of points of the dense cloud was elaborated with the ...
According to diverse theoretical methods, the existing single-frame detection methods can be roughly divided into the following several categories: methods based on background estimation filtering, local features, deep learning, principal component analysis, etc. The method based on background estimation ...
According to diverse theoretical methods, the existing single-frame detection methods can be roughly divided into the following several categories: methods based on background estimation filtering, local features, deep learning, principal component analysis, etc. The method based on background estimation ...