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Similarity Scores Based on Background Samples [chapter]

Lior Wolf, Tal Hassner, Yaniv Taigman
2010 Lecture Notes in Computer Science  
First, we define and evaluate the "Two-Shot Similarity" (TSS) score as an extension to the recently proposed "One-Shot Similarity" (OSS) measure.  ...  Both these measures utilize background samples to facilitate better recognition rates.  ...  Background-Sample Based Similarities with LDA The OSS and TSS scores are actually meta-similarities which can be fitted to work with almost any discriminative learning algorithm.  ... 
doi:10.1007/978-3-642-12304-7_9 fatcat:6osoctd3yrgqpg4zbmeow7x3ly

Considering scores between unrelated proteins in the search database improves profile comparison

Ruslan I Sadreyev, Yong Wang, Nick V Grishin
2009 BMC Bioinformatics  
Here we analyze a novel approach to estimate the statistical significance of profile similarity: the explicit consideration of background score distributions for each database template (subject).  ...  of homology detection; (ii) this increase is higher when the distributions are based on the scores to all known non-homologs of the subject rather than a small calibration subset of the database representatives  ...  In this setting, query-based background distributions and score averages (see Methods) are based on the query's non-homologs in the search database rather than on the calibration database.  ... 
doi:10.1186/1471-2105-10-399 pmid:19961610 pmcid:PMC3087343 fatcat:3w6nojjdtbhj5hn7jdl7ktet5e

An Automatic Voice Conversion Evaluation Strategy Based on Perceptual Background Noise Distortion and Speaker Similarity

Dong-Yan Huang, Lei Xie, Yvonne Siu Wa Lee, Jie Wu, Huaiping Ming, Xiaohai Tian, Shaofei Zhang, Chuang Ding, Mei Li, Quy Hy Nguyen, Minghui Dong, Haizhou LI
2016 9th ISCA Speech Synthesis Workshop  
This paper proposes an automatic voice conversion evaluation strategy based on perceptual background noise distortion and speaker similarity.  ...  We further use our strategy to select best converted samples from multiple voice conversion systems and our submission achieves promising results in the voice conversion challenge (VCC2016).  ...  The system selects the most similar to target voice sample based on speaker similarity score from the VC systems chosen by the average perceptual background noise distortion.  ... 
doi:10.21437/ssw.2016-8 dblp:conf/ssw/HuangXLWMTZDLHD16 fatcat:konaiiubtrhvxpplxy2j3vnv5u

Effective Unconstrained Face Recognition by Combining Multiple Descriptors and Learned Background Statistics

L. Wolf, T. Hassner, Y. Taigman
2011 IEEE Transactions on Pattern Analysis and Machine Intelligence  
(b) We demonstrate how semi-labeled background samples may be used to better evaluate image similarities. To this end we describe a number of novel, effective similarity measures.  ...  (c) We show how labeled background samples, when available, may further improve classification performance, by employing a unique pair-matching pipeline.  ...  The One-Shot and Two-Shot Similarity scores (OSS and TSS scores) introduced here (Section 4.1) are alternative approaches, designed to utilize "background" samples.  ... 
doi:10.1109/tpami.2010.230 pmid:21173442 fatcat:fywdeonmujc7zhkekfew67kzje

An Improved Particle Filter Tracking System Based on Colour and Moving Edge Information

Chao-Ju Chen, Wernhuar Tarng, Kuo-Hua Lo
2014 International Journal of Computer Science & Information Technology (IJCSIT)  
A colour-based particle filter can achieve the goal of effective target tracking, but it has some drawbacks when applied in the situations such as: the target and its background with similar colours, occlusion  ...  To deal with these problems, an improved particle filter tracking system based on colour and moving-edge information is proposed in this study to provide more accurate results in long-term tracking.  ...  If the score of the sample set does not exceed the threshold value, then the one with the highest score is selected as the seed to form the sample set.  ... 
doi:10.5121/ijcsit.2014.6407 fatcat:jhd625kk5rc7veot3y4agshniq

Multiscale anomaly detection using diffusion maps and saliency score

Gal Mishne, Israel Cohen
2014 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)  
Recently, we presented a multiscale approach to anomaly detection in images, combining diffusion maps for dimensionality reduction and a nearest-neighbor-based anomaly score in the reduced dimension.  ...  To overcome the limitations, a multiscale approach was proposed, which drives the sampling process to ensure separability of the anomaly from the background clutter.  ...  Saliency-based Anomaly Score In our previous paper [9] , we used an anomaly score based on a nearest-neighbor approach.  ... 
doi:10.1109/icassp.2014.6854115 dblp:conf/icassp/MishneC14 fatcat:syaahyksubcvxe7fw62jprigsa

Consistently Sampled Correlation Filters with Space Anisotropic Regularization for Visual Tracking

Guokai Shi, Tingfa Xu, Jie Guo, Jiqiang Luo, Yuankun Li
2017 Sensors  
Moreover, an optimization strategy based on the Gauss-Seidel method was developed for obtaining robust and efficient online learning.  ...  Most existing correlation filter-based tracking algorithms, which use fixed patches and cyclic shifts as training and detection measures, assume that the training samples are reliable and ignore the inconsistencies  ...  However, the establishment of these two strategies (the dense sampling and the continuous sample labels) is based on some assumptions.  ... 
doi:10.3390/s17122889 pmid:29231876 pmcid:PMC5750837 fatcat:opibwqipaff63lv6p4kh5ohq4u

Multi-sample pooling and illumina genome analyzer sequencing methods to determine gene sequence variation for database development

Rebecca L Margraf, Jacob D Durtschi, Shale Dames, David C Pattison, Jack E Stephens, Rong Mao, Karl V Voelkerding
2010 Journal of Biomolecular Techniques  
Based on background error rates, read coverage, simulated 30, 40, and 50 sample pool data, expected singleton allele frequencies within pools, and variant detection methods; >or=30 samples (which demonstrated  ...  After alignment, a 24-base quality score-screening threshold and 3; read end trimming of three bases yielded low background error rates with a 27% decrease in aligned read coverage.  ...  ACKNOWLEDGMENTS We thank David Nix, Brian Dalley, and Brad Cairns of the Huntsman Cancer Institute for running our sample libraries on the Illumina GA.  ... 
pmid:20808642 pmcid:PMC2922832 fatcat:jvurozffznegpkgm6myp2r34iy

Multi-channel wafer defect detection using diffusion maps

Gal Mishne, Israel Cohen
2014 2014 IEEE 28th Convention of Electrical & Electronics Engineers in Israel (IEEEI)  
We recently presented an anomaly detection approach based on geometric manifold learning techniques.  ...  This approach is data-driven, with the separation of the anomaly from the background arising from the intrinsic geometry of the image, revealed through the use of diffusion maps.  ...  This score has the following advantages: • Background regions which have similar diffusion coordinates, yet are spatially distant from one another in the image are suppressed.  ... 
doi:10.1109/eeei.2014.7005897 fatcat:gshgw2bjpfdidexwxxebqidyq4

Scene-Specific Pedestrian Detection for Static Video Surveillance

Xiaogang Wang, Meng Wang, Wei Li
2014 IEEE Transactions on Pattern Analysis and Machine Intelligence  
learning. (3) The confidence scores propagate among target samples according to their underlying visual structures. (4) Target samples with higher confidence scores have larger influence on training scene-specific  ...  During test, only the appearance-based detector is used without context cues. The effectiveness is demonstrated through experiments on two video surveillance datasets.  ...  Its confidence score becomes high after confidence propagation because some similar background patches are labeled as negative samples with high confidence scores.  ... 
doi:10.1109/tpami.2013.124 pmid:24356355 fatcat:dzfsu42jqvb4blbwumtaa32n6y

The SVM-Minus Similarity Score for Video Face Recognition

Lior Wolf, Noga Levy
2013 2013 IEEE Conference on Computer Vision and Pattern Recognition  
We present an effective way to discount pose induced similarities within such a framework, which is based on a newly introduced classifier called SVMminus.  ...  The method we propose belongs to a family of classifierbased similarity scores.  ...  SVMmodel is a stacking model learned on the training set. Computing the symmetric Matched Background Similarity for two sets, X1 and X2, given a set B of background samples.  ... 
doi:10.1109/cvpr.2013.452 dblp:conf/cvpr/WolfL13 fatcat:lzjv5wqmfrcfzobdpiwlx24zdq

Unsupervised Video Object Segmentation with Motion-Based Bilateral Networks [chapter]

Siyang Li, Bryan Seybold, Alexey Vorobyov, Xuejing Lei, C.-C. Jay Kuo
2018 Lecture Notes in Computer Science  
First, we propose a motion-based bilateral network to estimate the background based on the motion pattern of non-object regions.  ...  We classify graph nodes by defining and minimizing a cost function, and segment the video frames based on the node labels.  ...  Based on optical flow and objectness scores, a BNN identifies regions with motion patterns similar to those of non-object regions, which help classify static objects as background.  ... 
doi:10.1007/978-3-030-01219-9_13 fatcat:mi6u2taunncavfps2lipvk6rue

Fast-D: When Non-smoothing Color Feature Meets Moving Object Detection in Real-time

Md Alamgir Hossain, Md Imtiaz Hossain, Md Delowar Hossain, Ngo Thien Thu, Eui-Nam Huh
2020 IEEE Access  
Based on the amount of background motion, BG samples are replaced by a segmented BG pixel, and thresholds are updated as well.  ...  Then, like the BG samples update, the thresholds are also updated dynamically based on static/dynamic scenes in the background.  ... 
doi:10.1109/access.2020.3030108 fatcat:dcojmxefvjbpvhj7qxe6c2byne

chromVAR: Inferring transcription factor variation from single-cell epigenomic data [article]

Alicia N Schep, Beijing Wu, Jason Daniel Buenrostro, William J. Greenleaf
2017 bioRxiv   pre-print
We thank Caleb Lareau for valuable suggestions for improvements on the package as well as members of Greenleaf and Buenrostro labs for useful discussions.  ...  Differences in variability, bias corrected deviations, and deviation Z-scores based on number of background sets used. a) RMSD and normalized RMSD of variability when using a given number of background  ...  For each panel, the value of a different metric is shown based on varying the two parameters involved in background peak selection: (Rows) The number of bins (bs) used for grouping peaks based on GC content  ... 
doi:10.1101/110346 fatcat:gqqkz5ejejetnpng44ovepxwwq

An Investigation of Universal Background Sparse Coding Based Speaker Verification on TIMIT [article]

Xiao-Lei Zhang
2017 arXiv   pre-print
We used the cosine similarity and inner product similarity as the scoring methods of a trial. Experimental results show that UBSC is comparable to Gaussian mixture model.  ...  In this paper, we propose a universal background model, named universal background sparse coding (UBSC), for speaker verification.  ...  Comparing to GMM-UBM, UBSC does not make model assumptions on data distributions, since each base model of UBSC is a random sample of data.  ... 
arXiv:1509.07298v4 fatcat:u4km5qrglndxbijaxdzziqn65y
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