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Local Similarity-Based Fuzzy Multiple Kernel One-Class Support Vector Machine

Qiang He, Qingshuo Zhang, Hengyou Wang, Changlun Zhang, Tongqian Zhang
<span title="2020-10-28">2020</span> <i title="Hindawi Limited"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/y3fh56bfunh5fgneywwba6d4ke" style="color: black;">Complexity</a> </i> &nbsp;
The experimental results show that FMKOCSVM based on proposed local similarity membership is efficient and more robust to outliers than the ordinary multiple kernel OCSVMs.  ...  One-class support vector machine (OCSVM) is one of the most popular algorithms in the one-class classification problem, but it has one obvious disadvantage: it is sensitive to noise.  ...  Multiple Kernel One-Class Support Vector Machine.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1155/2020/8853277">doi:10.1155/2020/8853277</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/n2mgarbp3zblldugnliuezoara">fatcat:n2mgarbp3zblldugnliuezoara</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201102185648/http://downloads.hindawi.com/journals/complexity/2020/8853277.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/ca/ec/caec8949c34aba2a3fdab9275472226f01b4e2fe.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1155/2020/8853277"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> hindawi.com </button> </a>

Exploiting local and global geometric data relationships in Support Vector Data Description

Vasileios Mygdalis, Anastasios Tefas, Ioannis Pitas
<span title="">2016</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/jsl2pgelqja2piczru3a6nqkg4" style="color: black;">2016 23rd International Conference on Pattern Recognition (ICPR)</a> </i> &nbsp;
INTRODUCTION Support Vector Data Description (SVDD) is a support vector based one-class classifier, initially proposed in [1] .  ...  SUPPORT VECTOR DATA DESCRIPTION Let the vectors x i ∈ R D , i = 1, . . . , N form the target class, from which we wish to generate a one-class classification model, by employing the SVDD method.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/icpr.2016.7899685">doi:10.1109/icpr.2016.7899685</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/icpr/MygdalisTP16.html">dblp:conf/icpr/MygdalisTP16</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/h7iwl657vnf75gey3e7sj53zpu">fatcat:h7iwl657vnf75gey3e7sj53zpu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180724222919/https://research-information.bristol.ac.uk/ws/files/87903077/Ioannis_Pitas_Exploiting_local_and_global_geometric_data_reationships.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/ff/f1/fff195dafa19ca51ae7e97369b0ff7e693e71243.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/icpr.2016.7899685"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

pocl: A Performance-Portable OpenCL Implementation

Pekka Jääskeläinen, Carlos Sánchez de La Lama, Erik Schnetter, Kalle Raiskila, Jarmo Takala, Heikki Berg
<span title="2014-08-19">2014</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/6ni4hdyv7zdtzjxnzscp53l5ry" style="color: black;">International journal of parallel programming</a> </i> &nbsp;
The benefits of a common programming standard are clear; multiple vendors can provide support for application descriptions written according to the standard, thus reducing the program porting effort.  ...  At its core is a kernel compiler that can be used to exploit the data parallelism of OpenCL programs on multiple platforms with different parallel hardware styles.  ...  In addition to the financial supporters, the authors would also like to thank the constructive comments and references pointed out by the reviewers.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s10766-014-0320-y">doi:10.1007/s10766-014-0320-y</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/kcbbjqrcnnbqhkr4zsug5rk7wm">fatcat:kcbbjqrcnnbqhkr4zsug5rk7wm</a> </span>
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Multiple kernel-based discriminant analysis via support vectors for dimension reduction

Shan Zeng, Chongjun Gao, Xiuying Wang, Liang Jiang, David Feng
<span title="">2019</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q7qi7j4ckfac7ehf3mjbso4hne" style="color: black;">IEEE Access</a> </i> &nbsp;
INDEX TERMS Kernel discriminant analysis, multi-kernel SVM, support vectors. 35418 2169-3536  ...  A combination of multiple kernels is able to represent the complementary information of the original data from multiple views and thereby improves recognition performance.  ...  analysis (KDA) [26] ; 4) multiple kernel support vector machine (MKSVM) [33] ; and 5) discriminant analysis via support vectors (SVDA) [42] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2019.2904037">doi:10.1109/access.2019.2904037</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/u4bkha5gk5gxjou7q3fejfrku4">fatcat:u4bkha5gk5gxjou7q3fejfrku4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210429034533/https://ieeexplore.ieee.org/ielx7/6287639/8600701/08664467.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/53/84/53841f6336160aae189d49643d0bebdadbb05e33.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2019.2904037"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> ieee.com </button> </a>

SOFT BIOMETRICS: GENDER RECOGNITION FROM UNCONSTRAINED FACE IMAGES USING LOCAL FEATURE DESCRIPTOR

Olasimbo Ayodeji Arigbabu, Sharifah Mumtazah Syed Ahmad, Wan Azizun Wan Adnan, Saif Mahmood
<span title="2015-04-28">2015</span> <i title="UUM Press, Universiti Utara Malaysia"> Journal of Information and Communication Technology </i> &nbsp;
Our technique exploits the robustness of local feature descriptor to photometric variations to extract the shape description of the 2D face image using a single sample image per individual.  ...  However, image alignment increases the complexity and time of computation, while the use of multiple samples or having prior knowledge about data distribution is unrealistic in practical applications.  ...  In addition, we utilized Support Vector Machine (SVM) (Cortes & Vapnik, 1995) with different kernel functions to investigate the face gender recognition problem.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.32890/jict2015.14.0.8159">doi:10.32890/jict2015.14.0.8159</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/b2qf6d6vkzhspnotvwqr5lp724">fatcat:b2qf6d6vkzhspnotvwqr5lp724</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200816071052/http://e-journal.uum.edu.my/index.php/jict/article/download/8159/1173" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/4f/51/4f511f36a094da9bad2d71b1b20e30d6e4d3a4cc.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.32890/jict2015.14.0.8159"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

Hierarchical coarse-grained stream compilation for software defined radio

Yuan Lin, Manjunath Kudlur, Scott Mahlke, Trevor Mudge
<span title="">2007</span> <i title="ACM Press"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/h3qjmo5xyfe6fcrh4fogxmkkiq" style="color: black;">Proceedings of the 2007 international conference on Compilers, architecture, and synthesis for embedded systems - CASES &#39;07</a> </i> &nbsp;
We then present a coarse-grained dataflow compilation strategy that assigns a SDR protocol's DSP kernels onto multiple processors, allocates memory buffers, and determines an execution schedule that meets  ...  Due to this steep performance requirement, heterogeneous multiprocessor system-on-chip designs have been proposed to support SDR.  ...  Single-instruction multiple-data (SIMD) or vector processing is typically employed in the data processors.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/1289881.1289903">doi:10.1145/1289881.1289903</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/cases/LinKMM07.html">dblp:conf/cases/LinKMM07</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/n2rkbxygjfaiblioqg5nwwqqua">fatcat:n2rkbxygjfaiblioqg5nwwqqua</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170923002845/http://web.eecs.umich.edu/~tnm/trev_test/papersPDF/2007.09.Hierarchical_coarse-grained_stream_CASES.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/ef/bf/efbf7769601d8e492c4c35d79f1e8fc2142d6019.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/1289881.1289903"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> acm.org </button> </a>

Code generation from a domain-specific language for C-based HLS of hardware accelerators

Oliver Reiche, Moritz Schmid, Frank Hannig, Richard Membarth, Jürgen Teich
<span title="">2014</span> <i title="ACM Press"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/h4zelo33ojdfzbwajaf5qlthey" style="color: black;">Proceedings of the 2014 International Conference on Hardware/Software Codesign and System Synthesis - CODES &#39;14</a> </i> &nbsp;
As a remedy, in this work, we propose code generation techniques for C-based HLS from a common high-level DSL description targeting FPGAs.  ...  Our approach includes FPGA-specific memory architectures for handling point and local operators, numerous high-level transformations, and automatic test bench generation.  ...  Acknowledgment This work is partly supported by the German Research Foundation (DFG), as part of the Research Training Group 1773 "Heterogeneous Image Systems".  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/2656075.2656081">doi:10.1145/2656075.2656081</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/codes/ReicheSHMT14.html">dblp:conf/codes/ReicheSHMT14</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/xm6twrjwb5fcfgsq34nagmsmme">fatcat:xm6twrjwb5fcfgsq34nagmsmme</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20160120185207/https://www12.informatik.uni-erlangen.de/publications/reiche/reiche2014codes.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/81/ee/81ee8d80f21f8db1c4300e9eeef40394c3557a62.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/2656075.2656081"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> acm.org </button> </a>

Kernel Completion for Learning Consensus Support Vector Machines in Bandwidth-limited Sensor Networks
english

Sangkyun Lee, Christian Pölitz
<span title="">2014</span> <i title="SCITEPRESS - Science and and Technology Publications"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/liyq3gs4rneptl2m3dmjrh4qf4" style="color: black;">Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods</a> </i> &nbsp;
from local kernel matrices amongst peers.  ...  In this paper, we propose an alternative strategy for such scenarios, aiming to build a consensus support vector machine (SVM) in each sensor station by exchanging a small amount of sampled information  ...  ACKNOWLEDGEMENTS The authors acknowledge the support of Deutsche Forschungsgemeinschaft (DFG) within the Collaborative Research Center SFB 876 "Providing Information by Resource-Constrained Analysis",  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5220/0004829401130124">doi:10.5220/0004829401130124</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/icpram/LeeP14.html">dblp:conf/icpram/LeeP14</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/klmrnq24jba4vas53jnqugxvlu">fatcat:klmrnq24jba4vas53jnqugxvlu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20150131180229/http://www-ai.cs.uni-dortmund.de:80/PublicPublicationFiles/lee_poelitz_2014a.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/04/5f/045f0847007876ba13fc5a1fcf4263869fd8ecdd.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5220/0004829401130124"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Support-Vector-Based Hyperspectral Anomaly Detection Using Optimized Kernel Parameters

Prudhvi Gurram, Heesung Kwon
<span title="">2011</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q2cxanfrsvclzbz73u2mnqrxru" style="color: black;">IEEE Geoscience and Remote Sensing Letters</a> </i> &nbsp;
In this method, the support of a local background distribution is first non-parametrically learned by a technique called Support Vector Data Description (SVDD).  ...  The SVDD optimally models an enclosing hypersphere around the local background data in a high dimensional feature space associated with the Gaussian RBF kernel.  ...  SUPPORT VECTOR DATA DESCRIPTION (SVDD) Support Vector Data Description (SVDD), introduced in [11], characterizes the background data set by containing only the relevant data and excluding the superfluous  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/lgrs.2011.2155030">doi:10.1109/lgrs.2011.2155030</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/bwmvzzpksrbirewofsl6lnjdrq">fatcat:bwmvzzpksrbirewofsl6lnjdrq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170830032956/http://web.eecs.umich.edu/~hero/Data/MURI_VOI/Kwon_Kernel%20parameter%20optimization%20for%20SVDD.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/ac/15/ac15380ead550e035289c86b927095e6f8594662.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/lgrs.2011.2155030"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

OpenCL: A Parallel Programming Standard for Heterogeneous Computing Systems

John E. Stone, David Gohara, Guochun Shi
<span title="">2010</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/4hwwgwyqabardl76zzbexzcmhu" style="color: black;">Computing in science &amp; engineering (Print)</a> </i> &nbsp;
Acknowledgments David Gohara would like to thank Nathan Baker and Yong Huang for development and support of the APBS project. He also thanks Ian Ollmann and Aaftab Munshi for assistance with OpenCL.  ...  Performance experiments were made possible with hardware donations and OpenCL software provided by AMD, IBM, NVIDIA, and with support from NSF CNS grant 05-51665, the National Center for Supercomputing  ...  The inner loop uses vector types to process multiple grid points per work-item, and atom data is processed entirely from on-chip local memory, greatly increasing both arithmetic intensity and effective  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/mcse.2010.69">doi:10.1109/mcse.2010.69</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/21037981">pmid:21037981</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC2964860/">pmcid:PMC2964860</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/mjwguyjkyzautckp4cxqb6ms6u">fatcat:mjwguyjkyzautckp4cxqb6ms6u</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200507073138/http://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC2964860&amp;blobtype=pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/06/37/063713d5a4294a26bb6a6cad2782bb1b98aacaed.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/mcse.2010.69"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2964860" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Multiple Kernel Feature Line Embedding for Hyperspectral Image Classification

Chen
<span title="2019-12-04">2019</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kay2tsbijbawliu45dnhvyvgsq" style="color: black;">Remote Sensing</a> </i> &nbsp;
In the first multple kernel PCA (MKPCA) stage, the multple kernel learning method based on between-class distance and support vector machine (SVM) was used to find the kernel weights.  ...  However, since the conventional linear-based principle component analysis (PCA) pre-processing method in FLE cannot effectively extract the nonlinear information, the multiple kernel PCA (MKPCA) based  ...  In addition, the support vector machine (SVM) was applied in the proposed multiple kernel learning strategy which uses only the support vector set to determine the weight of each valid kernel function.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/rs11242892">doi:10.3390/rs11242892</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/xk6q73w7cfhurcj6l5vhkxwqdu">fatcat:xk6q73w7cfhurcj6l5vhkxwqdu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20191208121147/https://res.mdpi.com/d_attachment/remotesensing/remotesensing-11-02892/article_deploy/remotesensing-11-02892.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/f8/cd/f8cd0ea5747e62749053dda04adae79b38f38bcb.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/rs11242892"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

A Multiple Kernel Learning Algorithm for Cell Nucleus Classification of Renal Cell Carcinoma [chapter]

Peter Schüffler, Aydın Ulaş, Umberto Castellani, Vittorio Murino
<span title="">2011</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
We compare our results with an incremental version of MKL, support vector machines with single kernel (SVM) and voting.  ...  We consider a Multiple Kernel Learning (MKL) framework for nuclei classification in tissue microarray images of renal cell carcinoma.  ...  Also, we acknowledge financial support from the FET programme within the EU FP7, under the SIMBAD project (contract 213250).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-24085-0_43">doi:10.1007/978-3-642-24085-0_43</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/v46ggdnmyff47iy4krz6phjhfa">fatcat:v46ggdnmyff47iy4krz6phjhfa</a> </span>
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Support Vector One-Class Classification For Multiple-Distribution Data

Abdenour Bounsiar, Michael Madden
<span title="2010-08-23">2010</span> <i title="Zenodo"> Zenodo </i> &nbsp;
Get local data descriptions using any one-class support vector algorithm such as OCSVM. 3.  ...  Support Vector Data Description is another one-class support vector algorithm [19, 20] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5281/zenodo.42035">doi:10.5281/zenodo.42035</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/gbjsv7p75rhf5bcrzaogimaaje">fatcat:gbjsv7p75rhf5bcrzaogimaaje</a> </span>
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Soft Biometrics: Gender Recognition from Unconstrained Face Images using Local Feature Descriptor [article]

Olasimbo Ayodeji Arigbabu, Sharifah Mumtazah Syed Ahmad, Wan Azizun Wan Adnan, Salman Yussof, Saif Mahmood
<span title="2017-02-08">2017</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Our technique exploits the robustness of local feature descriptor to photometric variations to extract the shape description of the 2D face image using a single sample image per individual.  ...  However, image alignment increases the complexity and time of computation, while the use of multiple samples or having prior knowledge about data distribution is unrealistic in practical applications.  ...  The set of , that are non-zero are regarded as the support vectors.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1702.02537v1">arXiv:1702.02537v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/iaflvrcvybdbrasmozftyar2ny">fatcat:iaflvrcvybdbrasmozftyar2ny</a> </span>
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Tpetra, and the Use of Generic Programming in Scientific Computing

C.G. Baker, M.A. Heroux
<span title="">2012</span> <i title="Hindawi Limited"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/fw4azkpu65d2thmrwfkoawyxse" style="color: black;">Scientific Programming</a> </i> &nbsp;
Acknowledgements We would like to acknowledge the efforts of contributors to the Tpetra, Teuchos and Kokkos packages that have supported this work: Roscoe Bartlett (ORNL), Alan Williams (SNL), Carter Edwards  ...  Heterogeneous architecture support The typical usage of Tpetra falls under the singleprogram/multiple-data model, where all participating nodes are running the same program.  ...  Under this approach, a user authors a stateless serial kernel that is compiled and executed on the data associated with one or more Tpetra vectors.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1155/2012/693861">doi:10.1155/2012/693861</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/guejjt4ebzggzcucbnd4dtimee">fatcat:guejjt4ebzggzcucbnd4dtimee</a> </span>
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