{"id":54,"date":"2022-09-23T12:32:27","date_gmt":"2022-09-23T16:32:27","guid":{"rendered":"https:\/\/sites.charlotte.edu\/deephyd\/?page_id=54"},"modified":"2022-09-23T12:32:28","modified_gmt":"2022-09-23T16:32:28","slug":"publications","status":"publish","type":"page","link":"https:\/\/sites.charlotte.edu\/deephyd\/publications\/","title":{"rendered":"Publications"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\"><strong>Presentation<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\"><li>Chavan, V., Chen, S., Tang, W., Allen, C., Diemer, J., Shanmugam, N., Chen, T., Shukla, T., Slocum, Z., Lauffer, M. 2021. Effect of Scour on Stability of Drilled Pier (Pile) Foundation Using Three-Dimensional Finite Element Analysis Method. NCDOT Research &amp; Innovation Summit 2.0. Virtual. October 5-6, 2021.<\/li><li>Chavan, V. 2021. CASE STUDY: Finite Element Modelling of Phillips Road Bridge Pier Local Scour. Dissertation. University of North Carolina at Charlotte.<\/li><li>Chen, T., Tang, W., Chen, S., Allan, C., Diemer, J., Shukla, T., Shanmugam, N., Chavan, V., Lauffer, M.S. 2021. Deep learning-based 3D semantic segmentation: a practical case in hydrualic structures, Annual Meeting of the American Association of Geographers, Virtual Conference., April 7th, 2021.<\/li><li>Chen, T., Tang, W., Chen, S., Allan, C., Diemer, J., Shukla, T., Shanmugam, N., Chavan, V., Lauffer, M.S. 2021. Automated semantic segmentation of point cloud data driven by deep learning and 3D GIS. NCDOT Research &amp; Innovation Summit 2.0. Virtual. October 5-6, 2021.<\/li><li>Slocum, Z., Tang, W.,, Allan, C., Diemer, J., Chen, T., Chavan, V., Shanmugam, N., Shukla, T., Lauffer, M.S. 2021. A Web-based approach for the application of deep learning to the automated point cloud classification of hydraulic structures. NCDOT Research &amp; Innovation Summit 2.0. Virtual. October 5-6, 2021.<\/li><li>Shukla, T., Tang, W., Allan, C., Diemer, J., Chen, S., Chen, T., Slocum, Z., and Lauffer, M.S., 2021. The fusion of Unmanned Aerial System and sonar data for the assessment of scours of hydraulic structures, STRATUS, May 17th-19th, 2021.<\/li><li>Shukla, T., Tang, W., Allan, C., Diemer, J., Chen, S., Chen, T., Slocum, Z., Chavan, V., Shanmugam, N., Lauffer, M. 2021. Scour Monitoring of Hydraulic Structures using Unmanned Aerial System and Sonar. NCDOT Research &amp; Innovation Summit 2.0. Virtual. October 5-6, 2021.<\/li><li>Tang, W., Chen, S., Diemer, J., Allan, C., and Lauffer, M.S., 2021, Deep learning-based detection of 3D hydraulic structures from point cloud data: Acceleration via a cyberinfrastructure-enabled high-performance computing approach, Research Seminar of College of Computing and Informatics, UNC Charlotte, January 29th, 2021.<\/li><li>Chavan, V., Chen, S., Allan, C., Diemer, J., Tang, W., Shanmugam, N., Slocum, Z., Shukla, T., Chen, T., and Lauffer, M.S., 2020, Bridge Pier Scour-Induced Loading Effect Using Finite Element Modeling, NCDOT Research &amp; Innovation Virtual Summit, October 13th-14th, 2020. (poster presentation).&nbsp;&nbsp;&nbsp;<\/li><li>Chen, T., Tang, W., Chen, S., Allan, C., Diemer, J., Shukla, T., Slocum, Z., Shanmugam, N., Chavan, V., and Lauffer, M.S.,&nbsp; 2020. 3D Point Cloud Semantic Segmentation: A practical case in bridge detection. USGIF GEOINTegration Summit, September 28th, 2020 (poster presentation)<\/li><li>Chen, T., Tang, W., Chen, S., Chavan, V., Shanmugam, N., Slocum, Z., Shukla, T., Allan, C., Diemer, J., and Lauffer, M.S.,&nbsp; 2020. Deep Learning-based Semantic Segmentation of 3D Point Clouds: A Case Study for Hydraulic Structures and its components. NCDOT Research &amp; Innovation Virtual Summit, October 13th-14th, 2020. (Lightning Talk)<\/li><li>Shanmugam, N., Chen, S., Allan, C., Diemer, J., Tang, W., Chavan,V., Slocum, Z., Shukla, T., Chen, T., and Lauffer, M.S., 2020, Quantification of Bridge Pier Scour from 3D Point Cloud Data Using Spatial Interpolation, NCDOT Research &amp; Innovation Virtual Summit, October 13th-14th, 2020. (poster presentation).&nbsp;<\/li><li>Shukla, T., Allan, C., Tang, W., Chen, S., Diemer, J., Chen, T., Slocum, Z., Shanmugam, N., Chavan, V., and Lauffer, M.S., 2020, Bathymetric Surveys of Hydraulic Structures using unmanned aerial systems and sonar, NCDOT Research &amp; Innovation Virtual Summit, October 13th-14th, 2020. (poster presentation).<\/li><li>Tang, W., Chen, S., Diemer, J.,&nbsp; Allan, C., and Lauffer, M.S., 2020, The automation and acceleration of deep learning-based detection of 3D hydraulic structures from point cloud data: A cyberinfrastructure-enabled approach, NCDOT Research &amp; Innovation Virtual Summit, October 13th-14th, 2020.<\/li><li>Tang, Wenwu, Chen, Shen-en, Diemer, John, Allan, Craig, Lauffer, Matthew S., 2019, Deep learning-based classification of point cloud data for the automated detection of hydraulic structures driven by cyberinfrastructure-enabled high-performance computing., invited talk for the Colloquium of the Department of Geography at Virginia Tech on October 25<sup>th<\/sup>, 2019.<\/li><li>Chen, T., 2019,&nbsp;A case study to evaluate clusterODM toolkit for unmanned aerial vehicle mapping. <em>GIS Day Lighting Talk<\/em>, November 13th, 2019, Charlotte, NC.&nbsp;<\/li><li>Shukla, T. (2019). Spatial analysis of sonar data for scour assessment.&nbsp;<em>GIS Day Lighting Talk<\/em>, November 13th, 2019, Charlotte, NC.&nbsp;<\/li><li>Shanmugam, N. &amp; Chavan, V. (2019). LiDAR for bridge monitoring applications. <em>GIS Day Lighting Talk<\/em>, November 13th, 2019, Charlotte, NC.&nbsp;<\/li><li>Slocum, Z. (2019).&nbsp;UAS based data collection for GIS workflows. <em>GIS Day Lighting Talk<\/em>, November 13th, 2019, Charlotte, NC.<\/li><li>Shanmugam, N., Chen, S., Tang, W., Allan, C., Diemer, J., Chavan, V., Shukla, T., Chen, T., and Lauffer, M.S., 2019, Use of terrestrial LiDAR system for bridge condition assessment,&nbsp;<em>International Highway Engineering Exchange Program, September 9th, 2019,&nbsp; Asheville,&nbsp; NC.<\/em><\/li><li>Shanmugam, N., 2019, Introduction to LiDAR and Basic Point Cloud Analysis, <em>GIAN Course on Forensic Engineering and Failure Analysis,<\/em> National Institute of Technology Tiruchirappalli, Tiruchirappalli, Tamil Nadu, India, June 10th-21st, 2019.<\/li><li>Tang, W., Chen, S., Diemer, J., Allan, C., and Lauffer, M.S., 2019, DeepHyd: A deep learning-based artificial intelligence approach for the automated classification of hydraulic structures from LiDAR and Sonar data, <em>NCDOT Research &amp; Innovation Summit, May 7th, 2019, Greensboro, NC<\/em>.<\/li><li>Chen, T., Tang, W., Chen, S., Allan, C., Diemer, J., Shukla, T., Shanmugam, N., Chavan, V., Lauffer, M.S., 2019, Massive 3D scene reconstruction of hydraulic structures accelerated using high-performance computing, <em>NCDOT Research &amp; Innovation Summit, May 7th, 2019, Greensboro, NC<\/em>. (poster presentation).<\/li><li>Shukla, T., Chen, T., Tang, W., Chen, S., Allan, C., Diemer, J., Shanmugam, N., Chavan, V., and Lauffer, M.S., 2019, Bridge inspection based on unmanned aerial systems and photogrammetry techniques, <em>NCDOT Research &amp; Innovation Summit, May 7th, 2019, Greensboro, NC.<\/em> (poster presentation).<\/li><li>Chen, T., and Tang, W., 2019, When geospatial big data meets high performance computing in 3D GIS, <em>Annual Meeting of the American Association of Geographers, Washington D.C., April 3-7th, 2019<\/em><\/li><li>Shukla, T., Chen, T., and Tang, W., 2019, Topographical surveying using UAS photogrammetry, <em>Charlotte-Metropolitan GIS User Group Meeting, February 15th, 2019, Charlotte, NC, USA<\/em>.&nbsp;<\/li><\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Presentation Chavan, V., Chen, S., Tang, W., Allen, C., Diemer, J., Shanmugam, N., Chen, T., Shukla, T., Slocum, Z., Lauffer, M. 2021. Effect of Scour on Stability of Drilled Pier (Pile) Foundation Using Three-Dimensional Finite Element Analysis Method. NCDOT Research &amp; Innovation Summit 2.0. Virtual. October 5-6, 2021. Chavan, V. 2021. CASE STUDY: Finite Element [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-54","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/sites.charlotte.edu\/deephyd\/wp-json\/wp\/v2\/pages\/54","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sites.charlotte.edu\/deephyd\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/sites.charlotte.edu\/deephyd\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/sites.charlotte.edu\/deephyd\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.charlotte.edu\/deephyd\/wp-json\/wp\/v2\/comments?post=54"}],"version-history":[{"count":2,"href":"https:\/\/sites.charlotte.edu\/deephyd\/wp-json\/wp\/v2\/pages\/54\/revisions"}],"predecessor-version":[{"id":67,"href":"https:\/\/sites.charlotte.edu\/deephyd\/wp-json\/wp\/v2\/pages\/54\/revisions\/67"}],"wp:attachment":[{"href":"https:\/\/sites.charlotte.edu\/deephyd\/wp-json\/wp\/v2\/media?parent=54"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}