{"id":119,"date":"2013-04-04T16:04:59","date_gmt":"2013-04-04T16:04:59","guid":{"rendered":"https:\/\/beta.research.ece.ncsu.edu\/aros\/?page_id=119"},"modified":"2025-10-04T14:12:39","modified_gmt":"2025-10-04T14:12:39","slug":"publications","status":"publish","type":"page","link":"https:\/\/research.ece.ncsu.edu\/aros\/publications\/","title":{"rendered":"Publications"},"content":{"rendered":"

[et_pb_section fb_built=”1″ admin_label=”section” _builder_version=”4.16″ global_colors_info=”{}”][et_pb_row admin_label=”row” _builder_version=”4.16″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text admin_label=”Publications” _builder_version=”4.16″ text_font_size=”30″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” module_alignment=”left” hover_enabled=”0″ use_border_color=”off” border_color=”#ffffff” border_style=”solid” global_colors_info=”{}” sticky_enabled=”0″]<\/p>\n

\nPublications<\/strong><\/p>\n

[\/et_pb_text][et_pb_tabs _builder_version=”4.17.0″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” hover_enabled=”0″ global_colors_info=”{}” sticky_enabled=”0″][et_pb_tab title=”Journal and Articles” _builder_version=”4.17.0″ body_font=”||||” body_line_height=”2em” tab_font=”||||” tab_line_height=”2em” background_size=”initial” background_position=”top_left” background_repeat=”repeat” hover_enabled=”0″ body_line_height_tablet=”2em” body_line_height_phone=”2em” tab_line_height_tablet=”2em” tab_line_height_phone=”2em” global_colors_info=”{}” sticky_enabled=”0″]<\/p>\n

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  1. Y. Chen, F. Xiang, M. Hernandez, D. Carpenter, A. Bozkurt, E. Lobaton, “Robust Multimodal Cough Detection with Optimized Out-of-Distribution Detection for Wearables<\/strong><\/a>,” IEEE Journal of Biomedical and Health Informatics, 2025.<\/li>\n
  2. R. Soleimani, S. Guo, K.L. Haley, A. Jacks and E. Lobaton, “The Impact of Pause and Filler Word Encoding on Dementia Detection with Contrastive Learning<\/strong><\/a>,” Applied Sciences 2024, 14, 8879.<\/li>\n
  3. S. Banerjee, J. Reynolds, M. Taggart, M. Daniele, A. Bozkurt, E. Lobaton, \u201cQuantifying Visual Differences in Drought-Stressed Maize through Reflectance and Data-Driven Analysis,<\/a><\/strong>\u201d AI 2024, 5, 790-802<\/li>\n
  4. R. Soleimani, J. Barahona, Y. Chen, A. Bozkurt, M. Daniele, V. Pozdin, E. Lobaton, \u201cDeep Neural Sleep Staging: Recent Advances in Modeling and Interpretability<\/strong><\/a>,\u201d Physiologia 2024, 4, 1-42. https:\/\/doi.org\/10.3390\/physiologia4010001.<\/li>\n
  5. Y. Chen, P. Attri, J. Barahona, M. Hernandez, D. Carpenter, A. Bozkurt, E. Lobaton, “Robust Cough Detection with Out-of-Distribution Detection<\/strong><\/a>,” IEEE Journal of Biomedical and Health Informatics, doi: 10.1109\/JBHI.2023.3264783, 2023.<\/li>\n
  6. T. Richmond, J. Cole, G. Dangler, M. Daniele, T. Marchitto, E. Lobaton, “Forabot: Automated Planktic Foraminifera Isolation and Imaging<\/strong><\/a>,” Geochemistry, Geophysics, Geosystems, 23(12):e2022GC010689, 2022<\/li>\n
  7. B. Graham, J. Park, G. Billings, A. Hulse-Kemp, C. Haigler, E. Lobaton, \u201cEfficient Imaging and Computer Vision Detection of Two Cell Shapes in Young Cotton Fibers,<\/strong><\/a>\u201d Applications in Plant Sciences, 10(6): e11503, 2022.<\/li>\n
  8. R. Soleimani, E. Lobaton, “Enhancing Inference on Physiological and Kinematic Periodic Signals via Phase-Based Interpretability and Multi-Task Learning<\/strong><\/a>,” Information, 13, 326, 2022.<\/li>\n
  9. B. Zhong, R. da Silva, M. Tran, H. Huang and E. Lobaton, \u201cEfficient Environmental Context Prediction for Lower Limb Prostheses<\/strong><\/a>,\u201d IEEE Transactions on Systems, Man, and Cybernetics: Systems. 2021.<\/li>\n
  10. S. Haque, E. Lobaton, N. Nelson, G. C. Yencho, K. V. Pecota, R. Mierop, M. W. Kudenov, M. Boyette and C. M. Williams, \u201cComputer vision approach to characterize size and shape phenotypes of horticultural crops using high-throughput imagery<\/strong><\/a>,\u201d Computers and Electronics in Agriculture, vol. 182, 2021.<\/li>\n
  11. Q. Ge, T. Richmond, B. Zhong, T.M. Marchitto and E. Lobaton, “Enhancing the Morphological Segmentation of Microscopic Fossils Through Localized Topology-Aware Edge Detection<\/strong><\/a>,” Autonomous Robots, 2020.<\/li>\n
  12. J. Cole, A. Bozkurt and E. Lobaton, “Localization of Biobotic Insects Using Low-Cost Inertial Measurement Units<\/strong><\/a>,” Sensors 2020, 20, 4486.<\/li>\n
  13. B. Zhong, H. Huang and E. Lobaton, “Reliable Vision-Based Grasping Target Recognition for Upper Limb Prostheses<\/strong><\/a>,” in IEEE Transactions on Cybernetics, 2020.
    <\/em><\/li>\n
  14. B. Zhong, R. da Silva, M. Li, H. Huang and E. Lobaton, “Environmental Context Prediction for Lower Limb Prostheses with Uncertainty Quantification<\/strong><\/a>,” IEEE Transactions on Automation Science and Engineering, 2020.<\/li>\n
  15. F. Mohaddes, R. da Silva, F. Akbulut, Y. Zhou, A. Tanneeru, E. Lobaton, B. Lee and V. Misra, “A Pipeline for Adaptive Filtering and Transformation of Noisy Left-Arm ECG to Its Surrogate Chest Signal<\/strong><\/a>,” Electronics, 9(5), 2020.<\/li>\n
  16. P. Ramos-Gilardo, C. Reberg-Horton, A. M. Locke, S. Mirsky and E. Lobaton, \u201cDrought stress detection using low-cost Computer Vision System and Machine Learning techniques<\/strong><\/a>,\u201d IT Professional, vol. 22, no. 3, pp. 27-29, 1 May-June 2020.<\/li>\n
  17. K. Asadi, A. Kalkunte, A. Ender, S. Gotad, S. Maniyar, S. Anand, M. Noghabaei, K. Han, E. Lobaton, T. Wu, “An Integrated UGV-UAV System for Construction Site Data Collection<\/strong><\/a>,” Automation in Construction, 112, 2020.<\/li>\n
  18. K. Asadi, P. Chen, K. Han, T. Wu, E. Lobaton, \u201cLNSNet: Lightweight Navigable Space Segmentation for Autonomous Robots on Construction Sites<\/a>,<\/strong>” Data, 4(1), 2019.<\/li>\n
  19. R. Mitra, T.M. Marchitto, Q. Ge, B. Zhong, B. Kanakiya, M.S. Cook, J.S. Fehrenbacher, J.D. Ortiz, A. Tripati, E. Lobaton, “Automated species-level identification of planktic foraminifera using convolutional neural networks, with comparison to human performance<\/strong><\/a>,” Marine Micropaleontology, 147, 2019, pp 16-24.<\/li>\n
  20. N. Starliper, F. Mohammadzadeh, T. Songkakul, M. Hernandez, A. Bozkurt, E. Lobaton, “Activity-Aware Wearable System for Power-Efficient Prediction of Physiological Responses<\/a><\/strong>,” Sensors, 19(3), 2019, 441.<\/li>\n
  21. K. Asadi, H. Ramshankar, H. Pullagurla, A. Bhandare, S. Shanbhaq, P. Mehta, S. Kundu, K. Han, E. Lobaton, T. Wu, \u201cVision-Based Integrated Mobile Robotic System for Real-Time Applications in Construction<\/a><\/strong>,\u201d Automation in Construction Journal, 96, 2018, 470-482.<\/li>\n
  22. N. Lokare, B. Zhong and E. Lobaton, “Activity-Aware Physiological Response Prediction using Wearable Sensors<\/strong><\/a>,” Inventions, 2(4), 2017. [ Dataset<\/a> ]<\/li>\n
  23. A. Dirafzoon, A. Bozkurt and E. Lobaton, “A Framework for Mapping with Biobotic Insect Networks: From Local to Global Maps<\/a>,<\/strong>” Robotics and Autonomous Systems Journal, Volume 88, pp.79-96, 2017. [ Video 1<\/a> | Video 2<\/a> ]<\/li>\n
  24. G.M. Pomann, A. Staicu, E. Lobaton, A. Mejia, B. Dewey, D.S. Reich, E. Sweeney, R. Shinohara, \u201cFunctional Linear Model for Prediction of Magnetization Transfer Ratio in Multiple Sclerosis Lesions<\/strong><\/a>,\u201d Annals of Applied Statistics, 10(4), 2017, 2325-2348.<\/li>\n
  25. A. Dirafzoon, A. Bozkurt and E. Lobaton, “Geometric Learning and Topological Inference with Biobotic Networks<\/strong><\/a>,” IEEE Transactions on Signal and Information Processing over Networks,Volume 3, Issue 1, 2017.<\/li>\n
  26. A. Bozkurt, E. Lobaton, M. Sichitiu, \u201cA Biobotic Distributed Sensor Network for Under Rubble Search and Rescue<\/strong><\/a>,\u201d IEEE Computer Magazine, May 2016.<\/li>\n
  27. A. Bozkurt, E. Lobaton, M. Sichitiu, \u201cBiobotic Insect Sensor Networks for Search and Rescue<\/strong><\/a>,\u201d Journal of Homeland Defense & Security Information Analysis Center, 2(2), 2015.<\/li>\n
  28. A. Bozkurt, E. Lobaton, M. Sichitiu, T. Hedrick, T. Latif, A. Dirafzoon, E. Whitmire, A. Verderber, J. Marin, and H. Xiong, \u201cBiobotic Insect Swarm Based Sensor Networks for Search and Rescue<\/a>,<\/strong>\u201d Proceedings of SPIE, 9091, 2014.<\/li>\n
  29. P. Chen, K. Hong, N. Naikal, S.S. Sastry, D. Tygar, P. Yan, A.Y. Yang, L.C. Chang, L. Lin, S. Wang, E. Lobaton, S. Oh, P. Ahammad, \u201cA Low-Bandwidth Camera Sensor Platform with Applications in Smart Camera Networks<\/strong><\/a>\u201d, ACM Transactions on Sensor Networks, 2012.<\/li>\n<\/ol>\n

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    [\/et_pb_tab][et_pb_tab title=”Conferences” _builder_version=”4.16″ body_font=”||||” body_line_height=”2em” tab_font=”||||” tab_line_height=”2em” body_line_height_tablet=”2em” body_line_height_phone=”2em” tab_line_height_tablet=”2em” tab_line_height_phone=”2em” global_colors_info=”{}”]<\/p>\n

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      \n
    1. R. da Silva, N. Starliper, D.K. Bhosale, M. Taggart, R. Ranganath, T. Sarje, M. Daniele, A. Bozkurt, T. Rufty and E. Lobaton, “Feasibility Study of Water Stress Detection in Plants using a High-Throughput Low-Cost System<\/strong>,” IEEE Sensors, 2020.<\/li>\n
    2. T. Latif, L. Gonzalez, J. Dieffenderfer, Y. Liao, M. Hernandez, V. Misra, E. Lobaton and A. Bozkurt, “Preliminary Assessment of Human Biological Responses to Low-level Ozone<\/strong>,” IEEE Sensors, 2020.<\/li>\n
    3. P. Ramos-Giraldo, C. Reberg-Horton, S. Mirsky, E. Lobaton, A. Lock, E. Henriquez, A. Zuniga, A. Minin, “Low-Cost Camera to Detect Water Stress in Crops with Embedded Machine Learning<\/strong>,” IEEE Sensors 2020.<\/li>\n
    4. R. da Silva, E. Stone and E. Lobaton, \u201cA Feasibility Study of a Wearable Real-Time Notification System for Self-Awareness of body-Rocking Behavior<\/strong>,\u201d IEEE Engineering in Medicine and Biology Conference (EMBC), 2019.<\/li>\n
    5. L. Gonzalez, T. Paniagua, N. Starliper and E. Lobaton, \u201cSignal Quality for RR Interval Prediction on Wearable Sensors<\/strong>,\u201d IEEE Engineering in Medicine and Biology Conference (EMBC), 2019.<\/li>\n
    6. K. Asadi, R. Jain, Z. Qin, M. Sun, M. Noghabaei, J. Cole, K. Han and E. Lobaton, “Vision-based Obstacle Removal System for Autonomous Ground Vehicles using a Robotic Arm<\/strong>,” ASCE International Conference on Computing in Civil Engineering (i3CE), 2019.<\/li>\n
    7. F. Mohammadzadeh, C.S. Nam, and E. Lobaton, “Prediction of Physiological Response over Varying Forecast Lengths with a Wearable Health Monitoring Platform<\/strong>,” IEEE Engineering in Medicine and Biology Conference (EMBC), 2018.<\/li>\n
    8. L. Gonzalez, B. Zhong, and E. Lobaton, “A Framework for Physiological Response Prediction with Joint Activity State Optimization<\/strong>,” IEEE Engineering in Medicine and Biology Conference (EMBC), 2018.<\/li>\n
    9. J.P. Diaz-Paz, R.L. da Silva, B. Zhong, H. Huang, and E. Lobaton, “Visual Terrain Identification and Surface Inclination Estimation for Improving Human Locomotion with a Lower-Limb Prosthetic<\/strong>,” IEEE Engineering in Medicine and Biology Conference (EMBC), 2018.<\/li>\n
    10. K. Asadi, H. Ramshankar, H. Pullagurla, A. Bhandare, S. Shanbhag, P. Mehta, S. Kundu, K. Han, E. Lobaton, T. Wu, “Building an Integrated Mobile Robotic System for Real-Time Application in Construction,<\/strong>” Intl. Symp. on Automation and Robotics in Construction (ISARC), 2018.<\/li>\n
    11. B. Zhong, Q. Ge, B. Kanakiya, R. Mitra, T. Marchitto, E. Lobaton, “A Comparative Study of Image Classification Algorithms for Foraminifera Identification,<\/strong>”\u00a0IEEE Symp. Series on Computational Intelligence (SSCI), 2017.<\/li>\n
    12. Q. Ge and E. Lobaton, “Obstacle Detection in Outdoor Scenes based on Multi-Valued Stereo Disparity Maps,<\/strong>”\u00a0IEEE Symp. Series on Computational Intelligence (SSCI), 2017.<\/li>\n
    13. B. Zhong, Z. Qin, S. Yang, J. Chen, N. Mudrick, M. Taub, R. Azevedo, E. Lobaton, “Emotion Recognition with Facial Expressions and Physiological Signals,<\/strong>”\u00a0IEEE Symp. Series on Computational Intelligence (SSCI), 2017.<\/li>\n
    14. Q. Ge, B. Zhong, B. Kanakiya, R. Mitra, T. Marchitto, E. Lobaton, “Coarse-to-Fine Foraminifera Image Segmentation through 3D and Deep Features<\/strong>,”\u00a0IEEE Symp. Series on Computational Intelligence (SSCI), 2017.<\/li>\n
    15. N. Lokare, S. Samadi, B. Zhong, L. Gonzalez, F. Mohammadzadeh, E. Lobaton, “Energy-Efficient Activity Recognition via Multiple Time-Scale Analysis,<\/strong>”\u00a0IEEE Symp. Series on Computational Intelligence (SSCI), 2017.<\/li>\n
    16. J. Cole, T. Agcayazi, T. Latif, A. Bozkurt, E. Lobaton, “Speed Estimation based on Gait Analysis for Biobotic Agents,<\/strong>” IEEE Sensors Conf., 2017.<\/li>\n
    17. N. Lokare, T. Richmond, E. Lobaton, “Robust Trajectory-based Density Estimation for Geometric Structure Recovery,<\/strong>” European Signal Processing Conf. (EUSIPCO), 2017.<\/li>\n
    18. J. Cole, F. Mohammadzadeh, C. Bollinger, T. Latif, A. Bozkurt, E. Lobaton, “A Study on Motion Mode Identification for Cyborg Roaches,<\/strong>” Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP), 2017.<\/li>\n
    19. A. Dirafzoon, T. Latif, F. Gong, M. Sichitiu, A. Bozkurt, E. Lobaton, “Biobotic Motion and Behavior Analysis in Response to Directional Neurostimulation,<\/strong>” Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP), 2017. [ VIDEO<\/a> ]<\/li>\n
    20. A. Dirafzoon, N. Lokare and E. Lobaton, \u201cAction Classification from Motion Capture Data using Topological Data Analysis<\/strong>,\u201d IEEE Global Conf. on Signal and Information Processing (GlobalSIP), 2016.<\/li>\n
    21. N. Lokare, D. Benavides, S. Juneja and E. Lobaton, \u201cHierarchical Activity Clustering Analysis for Robust Graphical Structure Recovery<\/strong>,\u201d IEEE Global Conf. on Signal and Information Processing (GlobalSIP), 2016. [ VIDEO<\/a> ]<\/li>\n
    22. N. Lokare, L. Gonzalez and E. Lobaton, \u201cComparing the Effect of Muscle Activation in Wearable Devices using Wet and Textile Electrodes<\/strong>,\u201d IEEE Engineering in Medicine and Biology Conference (EMBC), 2016.<\/li>\n
    23. T. Latif, M. Yang, E. Lobaton and A. Bozkurt, \u201cPreliminary Statistical Assessment towards Characterization<\/strong> of Biobotic Control<\/strong>,\u201d IEEE Engineering in Medicine and Biology Conference (EMBC), 2016.<\/li>\n
    24. H. Xiong, T. Latif, E. Lobaton, A. Bozkurt and M. L. Sichitiu, \u201cCharacterization of RSS Variability for Biobot Localization using 802.15.4 Radios<\/strong>,\u201d IEEE Topical Meeting on Wireless Sensors and Sensor Networks (WiSNet), 2016.<\/li>\n
    25. Q. Ge and E. Lobaton, \u201cConsensus-Based Image Segmentation via Topological Persistence<\/strong>,\u201d Intl. Workshop on Differential Geometry in Computer Vision and Machine Learning (DIFF-CVML) at CVPR, 2016.<\/li>\n
    26. A. Dirafzoon, E. Lobaton and A. Bozkurt, \u201cDemonstration: Exploration and Topological Mapping with Hexbugs<\/strong>,\u201d Intl. Conf. on Information Processing in Sensor Networks (IPSN), 2015.<\/li>\n
    27. S. Chattopadhyay, Q. Ge. C. Wei and E. Lobaton, \u201cRobust Multi-Target Tracking in Outdoor Traffic Scenarios via Persistence Topology based Robust Motion Segmentation<\/strong>,\u201d IEEE Global Conf. on Signal and Information Processing (GlobalSIP), 2015.<\/li>\n
    28. A. Dirafzoon, J. Betthauser, J. Schornick, D. Benavides, and E. Lobaton, \u201cMapping of Unknown Environments using Minimal Sensing from a Stochastic Swarm<\/strong>,\u201d Intl. Conf. on Intelligent Robots and Systems (IROS), 2014. [ VIDEO <\/a>]<\/li>\n
    29. C. Wei, Q. Ge, S. Chattopadhyay, and E. Lobaton, \u201cRobust Obstacle Segmentation based on Topological Persistence in Outdoor Traffic Scenes,<\/strong>\u201d IEEE Symposium Series on Computational Intelligence (SSCI), 2014.<\/li>\n
    30. J. Betthauser, D. Benavides, J. Schornick, N. O\u2019Hara, J. Patel, J. Cole, and E. Lobaton, \u201cWolfBot: A Distributed Mobile Sensing Platform for Research and Educatio<\/strong>n,\u201d Zone 1 Conf of the ASEE, 2014. [ VIDEOS<\/a> ]<\/li>\n
    31. N. Lokare, Q. Ge, W. Snyder, Z. Jewell, S. Allibhai, and E. Lobaton, \u201cManifold Learning Approach to Curve Identification with Applications to Footprint Segmentation<\/strong>,\u201d IEEE Symposium Series on Computational Intelligence (SSCI), 2014.<\/li>\n
    32. Q. Ge, N. Lokare, and E. Lobaton, \u201cNon-Rigid Image Registration under non-Deterministic Deformation Bounds<\/strong>,\u201d Intl. Symposium on Medical Information Processing and Analysis (SIPAIM), 2014.<\/li>\n
    33. A. Bozkurt, E. Lobaton, M. Sichitiu, T. Hedrick, T. Latif, A. Dirafzoon, E. Whitmire, A. Verderber, J. Marin, and H. Xiong, \u201cBiobotic Insect Swarm Based Sensor Networks for Search and Rescue<\/strong>,\u201d Proceedings of SPIE, 9091, 2014.<\/li>\n
    34. A. Dirafzoon, and E. Lobaton, \u201cTopological Mapping of Unknown Environments using an Unlocalized Robotic Swarm<\/strong>,\u201d International Conference on Intelligent Robotics and Systems (IROS), 2013. [ VIDEO <\/a>]<\/li>\n
    35. G. Medina and E. Lobaton, \u201c3-D Visual Reconstruction: A System Perspective<\/strong>,\u201d International Symposium on Innovation and Technology (ISIT), Peru, 2011.<\/li>\n<\/ol>\n

      [\/et_pb_tab][et_pb_tab title=”Masters and PhD Thesis” _builder_version=”4.16″ body_font=”||||” body_line_height=”2em” tab_font=”||||” tab_line_height=”2em” background_size=”initial” background_position=”top_left” background_repeat=”repeat” body_line_height_tablet=”2em” body_line_height_phone=”2em” tab_line_height_tablet=”2em” tab_line_height_phone=”2em” global_colors_info=”{}”]<\/p>\n

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        \n
      1. B. Zhong, “Reliable Deep Learning for Intelligent Wearable Systems<\/strong><\/a>,” PhD NCSU, 2020.<\/li>\n
      2. L. Gonzalez, “Context Models for Physiological Response under Signal Quality<\/a>,<\/strong>” PhD NCSU, 2020.<\/li>\n
      3. F. Mohammadzadeh, “Power Efficient Physiological Response Prediction for Wearable Health Monitoring Platforms<\/a><\/strong>,” PhD NCSU, 2018.<\/li>\n
      4. N. Lokare, “A Framework for Activity Recognition and Prediction of Physiological Responses: Applications to Health Monitoring using Wearable Sensors<\/strong><\/a>,” PhD NCSU, 2017<\/li>\n
      5. A. Dirafzoon, “Mapping with Biobotic Insect Networks: A Geometric Estimation and Topological Data Analysis Framework<\/strong><\/a>,” PhD NCSU, 2016<\/li>\n
      6. A. Nag, “A Vision-Based Odometry Model for Adaptive Human-Robot Systems<\/a><\/strong>,” Masters NCSU, 2016.<\/li>\n
      7. H. Pandya, “Mobile Manipulator Based Framework for Dataset Generation and Algorithm Testing<\/strong><\/a>,” Masters NCSU, 2015.<\/li>\n
      8. C. Wei, “Driver Assistant System: Robust Segmentation based on Topological Persistent Analysis and Multi-target Tracking based on Dynamic Programming<\/strong><\/a>,” Masters NCSU, 2014.<\/li>\n
      9. S. Juneja, “Biomechanical and Gait Analysis of Human Motions using Lift-Assist Devices<\/strong><\/a>,” Masters NCSU, 2014.<\/li>\n<\/ol>\n

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        Publications   Y. Chen, F. Xiang, M. Hernandez, D. Carpenter, A. Bozkurt, E. Lobaton, “Robust Multimodal Cough Detection with Optimized Out-of-Distribution Detection for Wearables,” IEEE Journal of Biomedical and Health […]<\/p>\n","protected":false},"author":44,"featured_media":0,"parent":0,"menu_order":10,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":""},"class_list":["post-119","page","type-page","status-publish","hentry"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/research.ece.ncsu.edu\/aros\/wp-json\/wp\/v2\/pages\/119","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/research.ece.ncsu.edu\/aros\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/research.ece.ncsu.edu\/aros\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/research.ece.ncsu.edu\/aros\/wp-json\/wp\/v2\/users\/44"}],"replies":[{"embeddable":true,"href":"https:\/\/research.ece.ncsu.edu\/aros\/wp-json\/wp\/v2\/comments?post=119"}],"version-history":[{"count":39,"href":"https:\/\/research.ece.ncsu.edu\/aros\/wp-json\/wp\/v2\/pages\/119\/revisions"}],"predecessor-version":[{"id":1829,"href":"https:\/\/research.ece.ncsu.edu\/aros\/wp-json\/wp\/v2\/pages\/119\/revisions\/1829"}],"wp:attachment":[{"href":"https:\/\/research.ece.ncsu.edu\/aros\/wp-json\/wp\/v2\/media?parent=119"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}