Stereo matching is close to hitting a half-century of history, yet witnessed a rapid evolution in the last decade thanks to deep learning. While previous s
Disadvantages: the premise not completely correct, involved in many parameters which have a strong influence on the clustering result and relatively high time complexity. Table 9 Time complexity Full size table 4.5 Clustering Algorithm Based on Density The basic idea of this kind of clustering algori...
Lewis D D, Gale W A. A sequential algorithm for training text classifiers. In Proc. the 17th Annual International ACM-SIGIR Conference on Research and Development in Information Retrieval, July 1994, pp.3-12.. Google Scholar [20] Atlas L, Cohn D A, Ladner R E. Training connectionist netw...
Big data has a substantial role nowadays, and its importance has significantly increased over the last decade. Big data’s biggest advantages are providing knowledge, supporting the decision-making process, and improving the use of resources, services, a
, Isolation of tuft-2 cells based on CD45 expression using FACS. Shown is t-SNE of 332 EpCAM+/CD45+ FACS-sorted single cells (points; n = 3 pooled mice), coloured by unsupervised clustering (top left), the expression of the Tuft cell marker Dclk1 (top right), or the ...
designed an algorithm to detect which means of transport people would choose, including public transportation or private means, to infer how many people used which public transportation routes [121] throughout the day. The authors then proposed a model of the network of local transportation of Abid...
clustering algorithm has been developed and reported here. Our proposed method can easily determine the exact value of cutoff distancedcsince it has a direct impact on the results of the cluster centers. To increase the comparativeness for clustering data, the local densityρiand the separation ...
wheregenerates peaks when the steering vector is orthogonal to the noise subspace, indicating the arrival times of incoming signals. However, the MUSIC algorithm struggles resolving paths with small time-delay differences. It has been shown that the resolution still depends on the background noise an...
proposed SAPAS for identifying pAs from poly(A)-containing reads and quantifying pAs in peak regions determined by a parametric clustering algorithm [102]. They further applied SAPAS to the scRNA-seq data of GABAergic neurons and detected cell type-specific APA events and cell-to-cell modality...
(PCC) between the ranks of each model’s score within each group. As a result, we get a scalar value\(r_s \in [-1,1]\), indicating to what degree each algorithm performs equally on the generated data relative to the other algorithms, compared to their performance on real data. The...