{"@type": "dcat:Dataset", "accessLevel": "public", "accrualPeriodicity": "irregular", "bureauCode": ["006:55"], "contactPoint": {"fn": "Javier Bernal", "hasEmail": "mailto:javier.bernal@nist.gov"}, "description": "This is a software suite for computing optimal diffeomorphisms for elastic registration of curves. Algorithm adapt-DP is based on DP (dynamic programming) restricted to an adapting strip which is able to perform this computation in linear time. Description of Algorithm adapt-DP can be found in \"Fast Dynamic Programming for Elastic Registration of Curves\", Proceedings of the 2nd International Workshop on Differential Geometry in Computer Vision and Machine Learning (DIFF-CVML'16) in conjunction with Computer Vision Pattern Recognition Conference (CVPR) 2016, Las Vegas, Nevada, June 26-July 1, 2016. The zip file Fast_Dynamic_Programming.zip contains copies of implementation of Algorithm adapt-DP as Fortran files (a Matlab Fortran mex file and a Python compatible Fortran file) for execution with Matlab/Python, Matlab/Python test files for executing adapt-DP Matlab Fortran mex file and Python compatible Fortran file, respectively, example data files, usage instructions in README files, etc.", "distribution": [{"description": "zip file with copies of implementation of Algorithm adapt-DP as Fortran files (a Matlab Fortran mex file and a Python compatible Fortran file) for execution with Matlab/Python, Matlab/Python test file for executing adapt-DP Matlab Fortran mex file and Python compatible Fortran file, respectively, example data files, usage intructions in README files, etc. Algorithm adapt-DP is based on DP (dynamic programming) restricted to an adapting strip for computing in linear time optimal diffeomorphisms for elastic registration of curves. Description of Algorithm adapt-DP can be found in \"Fast Dynamic Programming for Elastic Registration of Curves\", Proceedings of the 2nd International Workshop on Differential Geometry in Computer Vision and Machine Learning (DIFF-CVML'16) in conjunction with Computer Vision Pattern Recognition Conference (CVPR) 2016, Las Vegas, Nevada, June 26-July 1, 2016.", "downloadURL": "https://math.nist.gov/~JBernal/Fast_Dynamic_Programming.zip", "format": "zip file", "mediaType": "application/pdf", "title": "Fast_Dynamic_Programming.zip"}, {"description": "Hash of the data file", "downloadURL": "https://data.nist.gov/od/ds/6FCA2C44E87B3E49E05324570681DCB11939/Fast_Dynamic_Programming.zip.sha256", "format": "SHA256", "mediaType": "text/plain", "title": "SHA256 Hash"}, {"description": "zip file with copies of implementation of Algorithm adapt-DP as Fortran files (a Matlab Fortran mex file and a Python compatible Fortran file) for execution with Matlab/Python, Matlab/Python test file for executing adapt-DP Matlab Fortran mex file and Python compatible Fortran file, respectively, example data files, usage intructions in README files, etc. Algorithm adapt-DP is based on DP (dynamic programming) restricted to an adapting strip for computing in linear time optimal diffeomorphisms for elastic registration of curves. Description of Algorithm adapt-DP can be found in \"Fast Dynamic Programming for Elastic Registration of Curves\", Proceedings of the 2nd International Workshop on Differential Geometry in Computer Vision and Machine Learning (DIFF-CVML'16) in conjunction with Computer Vision Pattern Recognition Conference (CVPR) 2016, Las Vegas, Nevada, June 26-July 1, 2016.", "downloadURL": "https://data.nist.gov/od/ds/6FCA2C44E87B3E49E05324570681DCB11939/Fast_Dynamic_Programming.zip", "format": "zip archive", "mediaType": "application/zip", "title": "Fast_Dynamic_Programming.zip"}, {"accessURL": "https://doi.org/10.18434/T4/1502501", "description": "DOI Access to Fast Dynamic Programming for Elastic Registration of Curves", "format": "text/html", "title": "DOI Access to Fast Dynamic Programming for Elastic Registration of Curves"}], "identifier": "6FCA2C44E87B3E49E05324570681DCB11939", "keyword": ["dynamic programming", "shape analysis", "elastic registration", "adapting strip"], "landingPage": "https://data.nist.gov/od/id/6FCA2C44E87B3E49E05324570681DCB11939", "language": ["en"], "license": "https://www.nist.gov/open/license", "modified": "2018-06-01 00:00:00", "programCode": ["006:045"], "publisher": {"@type": "org:Organization", "name": "National Institute of Standards and Technology"}, "references": ["https://dx.doi.org/10.1109/CVPRW.2016.137"], "theme": ["Mathematics and Statistics:Image and signal processing"], "title": "Fast Dynamic Programming for Elastic Registration of Curves"}