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Incorporating Measurement Error in Astronomical Object Classification [article]

Sarah Shy, Hyungsuk Tak, Eric D. Feigelson, John D. Timlin, G. Jogesh Babu
<span title="2022-05-02">2022</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
The proposed method first simulates perturbed realizations of the data from a Bayesian posterior predictive distribution of a Gaussian measurement error model.  ...  Most general-purpose classification methods, such as support-vector machine (SVM) and random forest (RF), fail to account for an unusual characteristic of astronomical data: known measurement error uncertainties  ...  ACKNOWLEDGMENTS SS and HT appreciate the Pennsylvania State University's Institute for Computational and Data Sciences for its computational support via the Roar supercomputer.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2112.06831v2">arXiv:2112.06831v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/wqghohprunfyjno2ye62m364pe">fatcat:wqghohprunfyjno2ye62m364pe</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220506214747/https://arxiv.org/pdf/2112.06831v2.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/8c/9c/8c9c0aa8bd2e211d593fc86e95f4437cfc5a5918.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2112.06831v2" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Using Soft Sensors as a Basis of an Innovative Architecture for Operation Planning and Quality Evaluation in Agricultural Sprayers

Elmer A. G. Peñaloza, Vilma A. Oliveira, Paulo E. Cruvinel
<span title="2021-02-10">2021</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/taedaf6aozg7vitz5dpgkojane" style="color: black;">Sensors</a> </i> &nbsp;
be used for control and optimization of the processes in pesticide application.  ...  The soft sensor provides, in one configuration, estimates of the quality of pesticide application at a certain time and, in the other, estimates of the appropriate sprayer-operating conditions, which can  ...  curve of real values with small estimation error bars.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s21041269">doi:10.3390/s21041269</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/33578915">pmid:33578915</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC7916728/">pmcid:PMC7916728</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/rsrqinktejfm5fxqiaqxb5xucu">fatcat:rsrqinktejfm5fxqiaqxb5xucu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210427175932/https://res.mdpi.com/d_attachment/sensors/sensors-21-01269/article_deploy/sensors-21-01269-v3.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/2a/98/2a9850ae5669d2d467d416d0b841f061d3b5e00d.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s21041269"> <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 target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7916728" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Distributed Classification of Gaussian Space–Time Sources in Wireless Sensor Networks

A. D'Costa, V. Ramachandran, A.M. Sayeed
<span title="">2004</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/onirm7ye2bfobnpwuwaopap5yu" style="color: black;">IEEE Journal on Selected Areas in Communications</a> </i> &nbsp;
Under mild conditions, the probability of error of all classification schemes (soft, hard, noisy) decays exponentially to zero with the number of independent node measurements-the error exponent depends  ...  Distributed signal processing techniques for classification of objects are studied assuming knowledge of sensor measurement statistics.  ...  We model the temporal signal at the th node as (6) where denotes a zero-mean complex circular white Gaussian noise process.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/jsac.2004.830896">doi:10.1109/jsac.2004.830896</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/vxefkjseejd3bjmon3bnssdeiq">fatcat:vxefkjseejd3bjmon3bnssdeiq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170921210207/https://minds.wisconsin.edu/bitstream/handle/1793/9368/file_1.pdf?sequence=1" 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/53/5b/535b9a8e9f662c561ede25c8a0e9c7e475018041.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/jsac.2004.830896"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Human-Centered Emotion Recognition in Animated GIFs [article]

Zhengyuan Yang, Yixuan Zhang, Jiebo Luo
<span title="2019-04-27">2019</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
The facial attention module exploits the strong relationship between GIF contents and human characters, and extracts frame-level visual feature with a focus on human faces.  ...  In this study, we demonstrate the importance of human related information in GIFs and conduct human-centered GIF emotion recognition with a proposed Keypoint Attended Visual Attention Network (KAVAN).  ...  As shown in the bar chart, the four coarse GIF categories are represented by four different bar colors, and each bar shows the intensity score for one of the 17 annotated emotions. show this potentially  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1904.12201v1">arXiv:1904.12201v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/yn7irz7tijgzdawxuy677gkrym">fatcat:yn7irz7tijgzdawxuy677gkrym</a> </span>
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Classification on Brain Functional Magnetic Resonance Imaging: Dimensionality, Sample Size, Subject Variability and Noise [chapter]

Jean Honorio
<span title="2014-09-03">2014</span> <i title="WORLD SCIENTIFIC"> Frontiers of Medical Imaging </i> &nbsp;
We propose a synthetic model for the systematic study of aspects such as dimensionality, sample size, subject variability and noise.  ...  Our aim in this chapter is to study the conditions for the reasonably good performance of classifiers on brain functional magnetic resonance imaging.  ...  We also include error bars at 90% significance level.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1142/9789814611107_0008">doi:10.1142/9789814611107_0008</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/zk25fh5nandotoz7h7kur6i56u">fatcat:zk25fh5nandotoz7h7kur6i56u</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180729110308/http://people.csail.mit.edu:80/jhonorio/fmrisynth_bookchapter14.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/df/34/df34a466777f1ea5edf76a7c78b21f234e955f6e.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1142/9789814611107_0008"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> worldscientific.com </button> </a>

Minimum Classification Error Training of Hidden Markov Models for Sequential Data in the Wavelet Domain

Diego Tomassi, Diego Milone, Liliana Forzani
<span title="2010-01-15">2010</span> <i title="IBERAMIA: Sociedad Iberoamericana de Inteligencia Artificial"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/5qve3fgne5dh3mzbzovoilyufm" style="color: black;">Inteligencia Artificial</a> </i> &nbsp;
The learning strategy relies on the minimum classification error approach and provides reestimation formulas for fully non-tied models.  ...  In the last years there has been increasing interest in developing discriminative training methods for hidden Markov models, with the aim to improve their performance in classification and pattern recognition  ...  Acknowledgements This work was carried out with financial support from UNL (CAI+D-012-72), ANPCyT (PAE-PICT-2007-00052) and CONICET.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.4114/ia.v13i44.1045">doi:10.4114/ia.v13i44.1045</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/x2v5avoe3rbc5oezy2pexqjqua">fatcat:x2v5avoe3rbc5oezy2pexqjqua</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170901120755/http://www.redalyc.org/pdf/925/92513154006.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/33/d3/33d3ff1162267c42820c52891ef6a7eea446485f.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.4114/ia.v13i44.1045"> <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>

Radial basis network estimator of oxygen content in the flue gas of debutanizer reboiler

Shafanda Nabil Sembodo, Nazrul Effendy, Kenny Dwiantoro, Nidlom Muddin
<span title="2022-06-01">2022</span> <i title="Institute of Advanced Engineering and Science"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/c3tlqqlmlrhohmjgwq5tzpde6m" style="color: black;">International Journal of Power Electronics and Drive Systems (IJPEDS)</a> </i> &nbsp;
The estimation of oxygen content with a soft sensor has been successfully carried out. The soft sensor generates an estimated mean square error of 0.216% with a standard deviation of 0.0242%.  ...  The radial basis function network model makes soft sensors adapt to data updates because of their advantage as a universal approximator.  ...  for this research.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.11591/ijece.v12i3.pp3044-3050">doi:10.11591/ijece.v12i3.pp3044-3050</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/5vzalzabmnhv7egc43ewcvrd7e">fatcat:5vzalzabmnhv7egc43ewcvrd7e</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220315040047/http://ijece.iaescore.com/index.php/IJECE/article/download/25972/15690" 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/c7/26/c726b9d5b58f87ab640b665560b458fd74aef8fc.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.11591/ijece.v12i3.pp3044-3050"> <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>

Parking space detection from video by augmenting training dataset

Wei Yu, Tsuhan Chen
<span title="">2009</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/anlh4tvwprcrtoxv5d4h6a7rye" style="color: black;">2009 16th IEEE International Conference on Image Processing (ICIP)</a> </i> &nbsp;
In this paper, we develop an image-based method to estimate the depth contour in parking areas. Our algorithm is an extension of the canonical appearance-based models for object recognition.  ...  The information is obtained by applying a fast block based stereo algorithm to estimate a rough disparity map. New "soft" samples are created to augment the training sample library.  ...  Classification We do experiments with two commonly used classification schemes: nearest neighbor and Gaussian model .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/icip.2009.5414333">doi:10.1109/icip.2009.5414333</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/icip/YuC09.html">dblp:conf/icip/YuC09</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/cvgcyu3q4fdbfeg7rdjm5qn63a">fatcat:cvgcyu3q4fdbfeg7rdjm5qn63a</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20120124194154/http://chenlab.ece.cornell.edu/people/weiyu/AutoParking.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/34/c4/34c473183f8511592b80c7e7c8753a814de29d14.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/icip.2009.5414333"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Gyro Denoising and Fusion Quaternion Attitude Estimation Based on Improved Least Squares

Chen Guang Wu, Zhang Lin Jing, Cheng Jian Hao, Fan Zi Yan
<span title="">2019</span> <i title="IEEE"> 2019 Chinese Automation Congress (CAC) </i> &nbsp;
for a comprehensive evaluation of the decision making process.  ...  Accurate classification of biological phenotypes is an essential task for medical decision making.  ...  GAUSSIAN PROCESSES CLASSIFICATION Gaussian processes classification [16] treats the sample values in the training data set as samples from a multivariate Gaussian distribution, defining a Gaussian process  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/cac48633.2019.8997261">doi:10.1109/cac48633.2019.8997261</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ee4ae2f35reyrn3w2rjnzccmvi">fatcat:ee4ae2f35reyrn3w2rjnzccmvi</a> </span>
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Effects of gender information in text-independent and text-dependent speaker verification

Anssi Kanervisto, Ville Vestman, Md Sahidullah, Ville Hautamaki, Tomi Kinnunen
<span title="">2017</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/rc5jnc4ldvhs3dswicq5wk3vsq" style="color: black;">2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)</a> </i> &nbsp;
The practice is to use the gender ground-truth and to train gender-dependent models. However, such information is not necessarily available, especially if speakers are remotely enrolled.  ...  conferenceObject info:eu-repo/semantics/acceptedVersion © IEEE All rights reserved ABSTRACT It is well-known that for speaker recognition task, genderdependent acoustic modeling performs better than genderindependent  ...  Due to Gender classification systems for the current study We have implemented three different gender classifiers. The two first ones use Gaussian mixture model (GMM) and i-vectors, respectively.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/icassp.2017.7953180">doi:10.1109/icassp.2017.7953180</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/icassp/KanervistoVSHK17.html">dblp:conf/icassp/KanervistoVSHK17</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/kkbjfckvirff7labbi3wyzm66u">fatcat:kkbjfckvirff7labbi3wyzm66u</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180721073817/https://erepo.uef.fi/bitstream/handle/123456789/4361/kanervisto_effects_2017.pdf;jsessionid=ADA0FE3048B0F4F8B419A51AB5948C90?sequence=1" 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/d0/4fd0223b1a93f40883613d4404fe44f76f20815d.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/icassp.2017.7953180"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

NLOS Identification and Mitigation Using Low-Cost UWB Devices

Valentín Barral, Carlos J. Escudero, José A. García-Naya, Roberto Maneiro-Catoira
<span title="2019-08-08">2019</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/taedaf6aozg7vitz5dpgkojane" style="color: black;">Sensors</a> </i> &nbsp;
, causing the estimation error to increase up to several meters.  ...  The results show that ML techniques are suitable to identify NLOS propagation conditions and also to mitigate the error of the estimates when there is LOS between the emitter and the receiver.  ...  It is based on the use of a surrogate model of the objective function f . Typical surrogate models for Bayesian optimization are Gaussian processes.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s19163464">doi:10.3390/s19163464</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/5sntjfm2afc6rdpn7frzsbghii">fatcat:5sntjfm2afc6rdpn7frzsbghii</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200305154032/https://ruc.udc.es/dspace/bitstream/handle/2183/23976/V.Barral_2019_NLOS_Identification_and_Mitigation_Using_Low-Cost_UWB_Devices.pdf;jsessionid=BC56621DD2EEFAA9511B853519D67AA2?sequence=3" 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/79/84/7984e583bfe11c6fd53d682e1c556d2b4f624536.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s19163464"> <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>

Deep learning for Gaussian process tomography model selection using the ASDEX Upgrade SXR system [article]

Francisco Matos, Jakob Svensson, Andrea Pavone, Tomas Odstrcil, Frank Jenko
<span title="2020-04-14">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Gaussian process tomography (GPT) is a method used for obtaining real-time tomographic reconstructions of the plasma emissivity profile in a tokamak, given some model for the underlying physical processes  ...  However, the computations involved in this particular step may become slow for data with high dimensionality, especially when comparing the evidence for many different models.  ...  The views and opinions expressed herein do not necessarily reflect those of the European Commission.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2004.06429v1">arXiv:2004.06429v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/jmd76h5q3zdndgz2uwf3e6uhiu">fatcat:jmd76h5q3zdndgz2uwf3e6uhiu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200416022740/https://arxiv.org/pdf/2004.06429v1.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] </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2004.06429v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Optimizing the operating conditions in a high precision industrial process using soft computing techniques

Emilio Corchado, Javier Sedano, Leticia Curiel, José R. Villar
<span title="2011-04-25">2011</span> <i title="Wiley"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/qcs6npiwtfgmnjz77pf7tz2zvu" style="color: black;">Expert systems</a> </i> &nbsp;
The three-step model has been tested with real data obtained for three different materials: aluminium, copper and hardened steel.  ...  The new three-phase industrial system presented in this study is capable of identifying a model for the laser-milling process based on low-order models.  ...  The authors would also like to thank the manufacturer of components for vehicle interiors, Grupo Antolin Ingenierı´a, S. A. as part of the MAGNO 2008-1028.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1111/j.1468-0394.2011.00588.x">doi:10.1111/j.1468-0394.2011.00588.x</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/5ai6auabijeuffcanjklbu3nru">fatcat:5ai6auabijeuffcanjklbu3nru</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200309070802/https://gredos.usal.es/bitstream/handle/10366/134383/optimizing_the_operating_conditions_in_a_highprecision_industrial_process_using_soft_computingtechniques.pdf;jsessionid=079A1F41CCC1D75E57534620BE4C884D?sequence=1" 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/b9/50/b950f8d47e4d7dd8928f5af1d16dbd5ea4e510b9.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1111/j.1468-0394.2011.00588.x"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Lung Field Segmenting in Dual-Energy Subtraction Chest X-ray Images

Robert E. Alvarez
<span title="2004-03-01">2004</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/7mxsagdhtrbahmfd6mjpsonp7a" style="color: black;">Journal of digital imaging</a> </i> &nbsp;
The reliability measure is able to detect contours with unusual lung outlines or errors in the processing.  ...  The reliability measure uses a statistical shape model to estimate the probability of occurrence of a contour. The method was experimentally tested with 30 human subject images.  ...  See the text for a discussion. figuration or errors in the processing.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s10278-003-1701-8">doi:10.1007/s10278-003-1701-8</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/15255518">pmid:15255518</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC3043963/">pmcid:PMC3043963</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/5yblkzdggjdo7gt4mm24olafmi">fatcat:5yblkzdggjdo7gt4mm24olafmi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200207221724/http://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC3043963&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/18/92/1892feda77ff243a32c5c5c7aa01ee95724a40bd.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s10278-003-1701-8"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3043963" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Exoskeleton-covered soft finger with vision-based proprioception and tactile sensing [article]

Yu She, Sandra Q. Liu, Peiyu Yu, Edward Adelson
<span title="2020-06-23">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
We train neural networks for proprioception and shape (box versus cylinder) classification using data from the embedded sensors.  ...  Finally, we assemble 2 of the fingers together to form a robotic gripper and successfully perform a bar stock classification task, which requires both shape and tactile information.  ...  The authors would also like to thank Branden Robert Romero and Shaoxiong Wang for their help in hardware manufacturing and algorithm development, and Achu Wilson for his help in setting up the two Raspberry  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1910.01287v2">arXiv:1910.01287v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/nr2judpmjzdk3pbm5emwsehmry">fatcat:nr2judpmjzdk3pbm5emwsehmry</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200904044845/https://arxiv.org/pdf/1910.01287v2.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/72/59/7259ca197deb5be5beb4ca3ba92175269683d148.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1910.01287v2" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>
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