scholarly journals High Speed Implementation of the Deformable Shape Tracking Face Alignment Algorithm

Author(s):  
Nikos Petrellis ◽  
Stavros Zogas ◽  
Panagiotis Christakos ◽  
Georgios Keramidas ◽  
Panagiotis Mousouliotis ◽  
...  
1984 ◽  
Vol 247 (3) ◽  
pp. E412-E419 ◽  
Author(s):  
L. S. Hibbard ◽  
R. A. Hawkins

Quantitative autoradiography is a powerful method for studying brain function by the determination of blood flow, glucose utilization, or transport of essential nutrients. Autoradiographic images contain vast amounts of potentially useful information, but conventional analyses can practically sample the data at only a small number of points arbitrarily chosen by the experimenter to represent discrete brain structures. To use image data more fully, computer methods for its acquisition, storage, quantitative analysis, and display are required. We have developed a system of computer programs that performs these tasks and has the following features: 1) editing and analysis of single images using interactive graphics, 2) an automatic image alignment algorithm that places images in register with one another using only the mathematical properties of the images themselves, 3) the calculation of mean images from equivalent images in different experimental serial image sets, 4) the calculation of difference images (e.g., experiment-minus-control) with the option to display only differences estimated to be statistically significant, and 5) the display of serial image metabolic maps reconstructed in three dimensions using a high-speed computer graphics system.


2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Mojtaba Mansour Abadi ◽  
Mitchell A. Cox ◽  
Rakan E. Alsaigh ◽  
Shaun Viola ◽  
Andrew Forbes ◽  
...  

AbstractFree-Space Optical (FSO) systems offer the ability to distribute high speed digital links into remote and rural communities where terrain, installation cost or infrastructure security pose critical hurdles to deployment. A challenge in any point-to-point FSO system is initiating and maintaining optical alignment from the sender to the receiver. In this paper we propose and demonstrate a low-complexity self-aligning FSO prototype that can completely self-align with no requirement for initial manual positioning and could therefore form the opto-mechanical basis for a mesh network of optical transceivers. The prototype utilises off-the-shelf consumer electrical components and a bespoke alignment algorithm. We demonstrate an eight fibre spatially multiplexed link with a loss of 15 dB over 210 m.


Author(s):  
Lin Cong ◽  
Zhang Ting ◽  
Lv Chongshan ◽  
Wu Wei ◽  
Zhan Xiang ◽  
...  

Author(s):  
Qingsong Tang ◽  
Qinqin Zhang ◽  
Xiaomeng Zhang ◽  
Zhenlin Cai ◽  
Xiangde Zhang

2017 ◽  
Author(s):  
Chong Tang ◽  
Yeming Xie ◽  
Wei Yan

AbstractSncRNA-Seq has become a routine for sncRNA profiling; however, software packages currently available are either exclusively for miRNA or piRNA annotation (e.g., miRDeep, miRanalyzer, Shortstack, PIANO), or for direct mapping of the sequence reads to the genome (e.g., Bowtie 2, SOAP and BWA), which tend to generate inaccurate counting due to repetitive matches to the genome or sncRNA homologs. Moreover, novel sncRNA variants in the sequencing reads, including those bearing small overhangs or internal insertions, deletions or mutations, are totally excluded from counting by these algorithms, leading to potential quantification bias. To overcome these problems, a comprehensive software package that can annotate all known small RNA species with adjustable tolerance towards small mismatches is needed. AASRA is based on our unique anchor alignment algorithm, which not only avoids repetitive or ambiguous counting, but also distinguishes mature miRNA from precursor miRNA reads. Compared to all existing pipelines for small RNA annotation, AASRA is superior in the following aspects: 1) AASRA can annotate all known sncRNA species simultaneously with the capability of distinguishing mature and precursor miRNAs; 2) AASRA can identify and allow for inclusion of sncRNA variants with small overhangs and/or internal insertions/deletions into the final counts; 3) AASRA is the fastest among all small RNA annotation pipelines tested. AASRA represents an all-in-one sncRNA annotation pipeline, which allows for high-speed, simultaneous annotation of all known sncRNA species with the capability to distinguish mature from precursor miRNAs, and to identify novel sncRNA variants in the sncRNA-Seq sequencing reads.Availability and Implementation:The AASRA software is freely available at https://github.com/biogramming/AASRA.


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