Filters








21,805 Hits in 3.6 sec

Recurrence textures for human activity recognition from compressive cameras

Kuldeep Kulkarni, Pavan Turaga
<span title="">2012</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/anlh4tvwprcrtoxv5d4h6a7rye" style="color: black;">2012 19th IEEE International Conference on Image Processing</a> </i> &nbsp;
The proposed feature is termed recurrence texture and is motivated from recurrence analysis of non-linear dynamical systems.  ...  In such a setting, we consider the problem of human activity recognition, which is an important inference problem in many security and surveillance applications.  ...  EXPERIMENTS For experiments, we choose the UMD Human Activity Dataset [22] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/icip.2012.6467135">doi:10.1109/icip.2012.6467135</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/icip/KulkarniT12.html">dblp:conf/icip/KulkarniT12</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/forvv2cu65azzk6m5eocbigemu">fatcat:forvv2cu65azzk6m5eocbigemu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20130418032627/http://www.public.asu.edu:80/~pturaga/papers/CSActivityRecn.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/a8/ac/a8ac2c9351ea4ad7c84742efa05b6040ad8b091d.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/icip.2012.6467135"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Page 856 of Behavior Research Methods Vol. 45, Issue 3 [page]

<span title="">2013</span> <i title="Psychonomic Society, Inc."> <a target="_blank" rel="noopener" href="https://archive.org/details/pub_behavior-research-methods" style="color: black;">Behavior Research Methods</a> </i> &nbsp;
Cross recurrence quantification of intopersonal postural activity. In M. A. Riley & G. C. Van Orden (Eds.), lUtorials in contemporary nonlinear methods for the behavioral sciences (pp. 142-177).  ...  Journal of the Association for Computing Machinery, 21, 168-178. Webber, C. L., Jr., & Zbilut, P. J. (2005). Recurrence quantification analysis of nonlinear dynamical systems. In M. A. Riley & G. C.  ... 
<span class="external-identifiers"> </span>
<a target="_blank" rel="noopener" href="https://archive.org/details/sim_behavior-research-methods_2013-09_45_3/page/856" title="read fulltext microfilm" 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> Archive [Microfilm] <div class="menu fulltext-thumbnail"> <img src="https://archive.org/serve/sim_behavior-research-methods_2013-09_45_3/__ia_thumb.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a>

Human activity recognition from mobile inertial sensors using recurrence plots [article]

Otávio A. B. Penatti, Milton F. S. Santos
<span title="2017-12-05">2017</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
In this paper, we present an approach for human activity recognition based on inertial sensors by employing recurrence plots (RP) and visual descriptors.  ...  Experiments for classifying human activities based on accelerometer data showed that the proposed approach obtains the highest accuracies, outperforming time- and frequency-domain features directly extracted  ...  human activity recognition.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1712.01429v1">arXiv:1712.01429v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/sqhxymbiuvchjkc2v4lwfoa5zm">fatcat:sqhxymbiuvchjkc2v4lwfoa5zm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201001022343/https://arxiv.org/pdf/1712.01429v1.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/ab/00/ab000e8d9392ccb5fe5dcc8bd21c713b33eec9c0.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1712.01429v1" 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>

A Self-Tuned Architecture for Human ActivityRecognition Based on a Dynamical RecurrenceAnalysis of Wearable Sensor Data

M.-A. Zervou, George Tzagkarakis, A. Panousopoulou, Panagiotis Tsakalides
<span title="2020-11-28">2020</span> <i title="Zenodo"> Zenodo </i> &nbsp;
Human activity recognition (HAR) is encountered ina plethora of applications, such as pervasive health care systemsand smart homes.  ...  feature extraction and activity recognition bymodeling directly the inherent dynamics of wearable sensordata in higher-dimensional phase spaces, which encode staterecurrences for each individual activity  ...  To this end, recurrence quantification analysis (RQA) [13] will be exploited to perform a sophisticated nonlinear analysis of sensor streams, while being also able to treat nonstationary and short data  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5281/zenodo.4294527">doi:10.5281/zenodo.4294527</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/3gekyhhknra2pkfiwlg5lc57k4">fatcat:3gekyhhknra2pkfiwlg5lc57k4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201130211207/https://zenodo.org/record/4294528/files/2019-EUSIPCO-Zervou.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/a9/ed/a9edcc8826f2642dae13aaf6db8ca4ef7d7649ea.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5281/zenodo.4294527"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> zenodo.org </button> </a>

EEG-based human emotion recognition using entropy as a feature extraction measure

Pragati Patel, Raghunandan R, Ramesh Naidu Annavarapu
<span title="2021-10-05">2021</span> <i title="Springer-Verlag"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/mkrnpcnuxraprbvqo4hu6naxfy" style="color: black;">Brain Informatics</a> </i> &nbsp;
This review aims to give a brief summary of various entropy-based methods used for emotion classification hence providing insights into EEG-based emotion recognition.  ...  EEG closely measures the electrical activities of the brain (a nonlinear system) and hence entropy proves to be an efficient feature in extracting meaningful information from raw brain waves.  ...  Acknowledgements The authors acknowledge Pondicherry University for financial support through University Fellowship.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1186/s40708-021-00141-5">doi:10.1186/s40708-021-00141-5</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/34609639">pmid:34609639</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/c5qogfsptbhwxjh4otnzdsng6m">fatcat:c5qogfsptbhwxjh4otnzdsng6m</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20211007124135/https://braininformatics.springeropen.com/track/pdf/10.1186/s40708-021-00141-5.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/5c/9a/5c9ad443f68183a0a6c0a28dcf1d1a1c12f6c5a2.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1186/s40708-021-00141-5"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> springer.com </button> </a>

Automatic measure of imitation during social interaction: A behavioral and hyperscanning-EEG benchmark

Emilie Delaherche, Guillaume Dumas, Jacqueline Nadel, Mohamed Chetouani
<span title="">2015</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/6r4znskbk5h2ngu345slqsm6eu" style="color: black;">Pattern Recognition Letters</a> </i> &nbsp;
Investigating its neural underpinnings has been greatly facilitated through the development of hyperscanning, a neuroimaging technique allowing to record simultaneously the brain activity of multiple humans  ...  Social neuroscience shows a growing interest for the study of social interaction.  ...  for her generous help in the EEG preparation.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.patrec.2014.09.002">doi:10.1016/j.patrec.2014.09.002</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/muniepodtrhhth6lvluk2ivfty">fatcat:muniepodtrhhth6lvluk2ivfty</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20150919063825/http://www.isir.upmc.fr/files/2015ACLI3184.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/3e/65/3e654da5f98f9935dad6040dd86e85d4a44adff6.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.patrec.2014.09.002"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>

Page 281 of The Journal of Investigative Dermatology Vol. 107, Issue 2 [page]

<span title="">1996</span> <i title="Nature Publishing Group"> <a target="_blank" rel="noopener" href="https://archive.org/details/pub_journal-of-investigative-dermatology" style="color: black;">The Journal of Investigative Dermatology</a> </i> &nbsp;
OF AN IMAGE ANALYSIS METHOD FOR THE QUANTIFICATION OF THE INTRACELLULAR MELANIN IN TRANSMISSION ELECTRON MICROSCOPY (TEM). is, J.- = ile.  ...  Biochemical analysis has shown that salmon GM2 structure is strictly identical to human melanoma GM2.  ... 
<span class="external-identifiers"> </span>
<a target="_blank" rel="noopener" href="https://archive.org/details/sim_journal-of-investigative-dermatology_1996-08_107_2/page/281" title="read fulltext microfilm" 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> Archive [Microfilm] <div class="menu fulltext-thumbnail"> <img src="https://archive.org/serve/sim_journal-of-investigative-dermatology_1996-08_107_2/__ia_thumb.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a>

Nonlinear methods to quantify Movement Variability in Human-Humanoid Interaction Activities [article]

Miguel Xochicale, Chirs Baber
<span title="2021-03-25">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Hence this work might enhance the development of better diagnostic tools for applications in rehabilitation and sport science for skill performance or new forms of human-humanoid interaction for quantification  ...  We therefore investigate nonlinear methods such as reconstructed state space (RSSs), uniform time-delay embedding, recurrence plots (RPs) and recurrence quantification analysis (RQAs) with real-world time-series  ...  accelerate the analysis of the nonlinear time series in this work.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1810.09249v6">arXiv:1810.09249v6</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/lftrotxcifew7nlcy54uxv3nnm">fatcat:lftrotxcifew7nlcy54uxv3nnm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210325064404/https://arxiv.org/pdf/1810.09249v5.pdf" title="fulltext PDF download [not primary version]" 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] <span style="color: #f43e3e;">&#10033;</span> <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/2c/25/2c25ed4088d2ef7e8f42c1418b9642e5335b3a88.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1810.09249v6" 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>

GestureKeeper: Gesture Recognition for Controlling Devices in IoT Environments [article]

Vasileios Sideridis, Andrew Zacharakis, George Tzagkarakis, Maria Papadopouli
<span title="2019-03-15">2019</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
To address this problem, GestureKeeper identifies the start of a gesture by exploiting the underlying dynamics of the associated time series using a recurrence quantification analysis (RQA).  ...  RQA is a powerful method for nonlinear time-series analysis, which enables the detection of critical transitions in the system's dynamical behavior.  ...  (HGR), human activity recognition (HAR) [5] - [9] and even in human writing recognition [10] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1903.06643v1">arXiv:1903.06643v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/p2kugh5njjdjtoffa7byd7g4ei">fatcat:p2kugh5njjdjtoffa7byd7g4ei</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200909132555/https://arxiv.org/pdf/1903.06643v1.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/a4/62/a4626de46a2f821a5cd39d6cd5af70e7131e5aea.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1903.06643v1" 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>

Recurrent Transformation of Prior Knowledge Based Model for Human Motion Recognition

Cheng Xu, Jie He, Xiaotong Zhang, Haipiao Cai, Shihong Duan, Po-Hsuan Tseng, Chong Li
<span title="">2018</span> <i title="Hindawi Limited"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/3wwzxqpotbc73bzpemzybzg7ee" style="color: black;">Computational Intelligence and Neuroscience</a> </i> &nbsp;
Motion related human activity recognition using wearable sensors can potentially enable various useful daily applications.  ...  Knowledge-based Decision Tree (RT-PKDT) model for recognition of specific human motions.  ...  For example, Ordóñez and Roggen [19] proposed a generic deep framework (DeepConvLSTM) for activity recognition based on convolutional and LSTM recurrent units.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1155/2018/4160652">doi:10.1155/2018/4160652</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/29568309">pmid:29568309</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC5820668/">pmcid:PMC5820668</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/sqn3efbhs5gsbhtbhnx5faevzu">fatcat:sqn3efbhs5gsbhtbhnx5faevzu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200209225237/http://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC5820668&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/62/92/6292461ba0c551c15688a4d78438672bc25ce3c9.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1155/2018/4160652"> <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> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5820668" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Increased expression of programmed death ligand 1 (PD-L1) in human pituitary tumors

Yu Mei, Wenya Linda Bi, Noah F. Greenwald, Ziming Du, Nathalie Y.R. Agar, Ursula B. Kaiser, Whitney W. Woodmansee, David A. Reardon, Gordon J. Freeman, Peter E. Fecci, Edward R. Laws, Sandro Santagata (+2 others)
<span title="2016-09-17">2016</span> <i title="Impact Journals, LLC"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/yubgl6cdcrekxpjzhshpw23l3i" style="color: black;">OncoTarget</a> </i> &nbsp;
Moreover, primary pituitary adenomas harbored higher levels of PD-L1 mRNA compared to recurrent tumors.  ...  Conclusions: Human pituitary adenomas harbor PD-L1 across subtypes, with significantly higher expression in functioning adenomas compared to non-functioning adenomas.  ...  ACKNOWLEDGMENTS We thank members of the Santagata and Agar labs for helpful discussion. We thank Dr. Gordon J. Freeman at Dana-Farber Cancer Institute for providing PD-1 and PD-L1 antibodies.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.18632/oncotarget.12088">doi:10.18632/oncotarget.12088</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/27655724">pmid:27655724</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC5363530/">pmcid:PMC5363530</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/fyzkijhgxngqdau3so2c3ugtdy">fatcat:fyzkijhgxngqdau3so2c3ugtdy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180724034204/https://dash.harvard.edu/bitstream/handle/1/32072073/5363530.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/71/06/7106fd4cf98ae8e7362ddfc633f86cef59baad24.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.18632/oncotarget.12088"> <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> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5363530" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Vulnerable Road User Detection Using Smartphone Sensors and Recurrence Quantification Analysis

Huthaifa I. Ashqar, Mohammed Elhenawy, Mahmoud Masoud, Andry Rakotonirainy, Hesham A. Rakha
<span title="">2019</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/cfmch5qrm5ckxpkho4uhbkgznm" style="color: black;">2019 IEEE Intelligent Transportation Systems Conference (ITSC)</a> </i> &nbsp;
This study explores the use of low-power smartphone sensors and the Recurrence Quantification Analysis (RQA) features for this task.  ...  With the fast advancements of the Autonomous Vehicle (AV) industry, detection of Vulnerable Road Users (VRUs) using smartphones is critical for safety applications of Cooperative Intelligent Transportation  ...  Recurrence Quantification Analysis (RQA) A traditional practice in transportation mode recognition is extracting features from the time domain that can be input to state-of-the-art algorithms for classification  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/itsc.2019.8917520">doi:10.1109/itsc.2019.8917520</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/itsc/AshqarEMRR19.html">dblp:conf/itsc/AshqarEMRR19</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/nbq77s5jtja5tdxj3eqq3ufnoa">fatcat:nbq77s5jtja5tdxj3eqq3ufnoa</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200616001820/https://arxiv.org/ftp/arxiv/papers/2006/2006.06941.pdf" title="fulltext PDF download [not primary version]" 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] <span style="color: #f43e3e;">&#10033;</span> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/itsc.2019.8917520"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Nonlinear Analysis to Quantify Movement Variability in Human-Humanoid Interaction

Miguel Xochicale, Professor Chris Baber, Professor Martin Russell
<span title="2019-08-30">2019</span> <i title="Zenodo"> Zenodo </i> &nbsp;
Methods are explored to determine embedding parameters, reconstructed state spaces, recurrence plots and recurrence quantification analysis.  ...  Additionally, this thesis presents three dimensional surface plots of recurrence quantification analysis with which to consider the variation of embedded parameters and recurrence thresholds.  ...  Recurrence Quantification Analysis In this section is shown Recurrence Quantification Analysis ( ( Sensors and activities (1 0,1 ) (1 0,1 ) ( It can also be noted that the  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5281/zenodo.3384145">doi:10.5281/zenodo.3384145</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/4acixy47brbu3n2xmya3qidjqq">fatcat:4acixy47brbu3n2xmya3qidjqq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200307125004/https://zenodo.org/record/3384145/files/thesis.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 noreferrer" href="https://doi.org/10.5281/zenodo.3384145"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> zenodo.org </button> </a>

Table of Contents

<span title="">2019</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q2z26obphvchndqieqd65vltle" style="color: black;">IEEE journal of biomedical and health informatics</a> </i> &nbsp;
Sun 1141 RACE-Net: A Recurrent Neural Network for Biomedical Image Segmentation . . . . . . . A. Chakravarty and J.  ...  Ahmad 1066 Analysis and Quantification of Repetitive Motion in Long-Term Rehabilitation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  ...  Pattern Classification for Gastrointestinal Stromal Tumors by Integration of Radiomics and Deep Convolutional Features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Z.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/jbhi.2019.2910329">doi:10.1109/jbhi.2019.2910329</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/scohod5zjbbanmdvwgyltf5pgy">fatcat:scohod5zjbbanmdvwgyltf5pgy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201108062920/https://ieeexplore.ieee.org/ielx7/6221020/8705605/08705606.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/f0/ad/f0adf391671d38c857f21d37872af33d79de81aa.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/jbhi.2019.2910329"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Evaluating the Determinism of Brain Signals Using Recurrence Chaotic Features in Positive, Negative and Neutral Emotional States in the Sources Achieved From ICA Algorithm

Mehdi Abdossalehi, Ali Motie Nasrabadi
<span title="">2017</span> <i title="Shahid Beheshti University of Medical Sciences"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/dmvumtoe45aa3ifyapmbmlfyai" style="color: black;">International Clinical Neuroscience Journal</a> </i> &nbsp;
Quantification Analysis (RQA) are extracted as representative of determination.  ...  Method: It is assumed that the brain draws on several independent sources in any activity that are observable by independent component algorithm (ICA).  ...  The recurrence quantification analysis was developed in order to quantify differently appearing recurrence plots (RPs) based on the small-scale structures therein.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.22037/icnj.v4i2.17165">doi:10.22037/icnj.v4i2.17165</a> <a target="_blank" rel="external noopener" href="https://doaj.org/article/534f3c7e2a754543bf2b501151fbe8e0">doaj:534f3c7e2a754543bf2b501151fbe8e0</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/fubzyrw5cjfi3bprvqc5bmmuai">fatcat:fubzyrw5cjfi3bprvqc5bmmuai</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200115145238/http://journals.sbmu.ac.ir:80/Neuroscience/article/download/17165/6" 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/50/88/5088683f080e28c419d007d1cf32fb77f4ff230b.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.22037/icnj.v4i2.17165"> <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>
&laquo; Previous Showing results 1 &mdash; 15 out of 21,805 results