min‐sum algorithmnormalized MSAmodified NMSAorder statisticsIn this paper, we propose a new modified normalized min-sum algorithm for low-density parity-check decoding. Instead of normalizing the results of the
0. We use a greedy algorithm in computing the selection vector. We initially select the full set, i.e. W(0)={1,1,…,1}. Then at each iteration i, we remove from W(i-1) the feature which maximizes F(W(i))-F(W(i-1)). The algorithm stops when the desired number of ...
The cloud detection algorithm available from Google Earth Engine (GEE) was applied to mitigate the cloud issues of Sentinel-2 surface reflectance data based on the spectral band “QA60″ (Nguyen et al., 2021). 2.6. Statistical analyses To avoid potential large deviation from the cosine ...
based on the biological experiments, Faghihi et al. [16] found that the expression of BACE1-AS can promote the rapid feed forward regulation of β-secretase in Alzheimer’s disease. Applying the RT-PCR technology and Northern blot analysis...
To digitize the mined traces, we used Engauge Digitizer, a multiplatform open-source software (digitizer.sourceforge.net). We implemented a custom Python algorithm, Trace Reconstructor, as part of our Synapse Modeling Utility, to extract a consistent set of data points from each synaptic event, ...
3. Approach: TokenCut The TokenCut algorithm can be used to predict bounding boxes that locate a salient object in an image. Our approach, illustrated in Fig. 2, is based on a graph where the nodes are tokens and the edges are similarities between the...
Normalized Cuts-ppt
The algorithm starts by fitting a square box of size ‘r x r' (i.e., filter) on the top-left corner of the input image (e.g., a remote-sensed image such as NDVI). The size ‘r' of the filter is adjusted regarding the three spatial scales. In our case, r = 21, r = 61,...
Matching two graphs is traditionally formulated as an optimization problem which is solved by the graduated assignment algorithm (Gold and Rangarajan1996), the integer projected fixed point method (Leordeanu et al.2009), the spectral matching methods (Leordeanu and Hebert2005; Cour et al.2007), the...
feature size search window(s) Flint fast NCC 1 min. 40 seconds 16 seconds (subpixel=1) n/a 21 seconds (subpixel=8) Table 2: Measured tracking times on a short sequence using the commercial Flint system and the algorithm described in the text. These are wall-clock times obtained on an...