Reproducible Research in Pattern Recognition  Second International Workshop, RRPR 2018, Beijing, China, August 20, 2018, Revised Selected Papers /  [electronic resource] : 
edited by Bertrand Kerautret, Miguel Colom, Daniel Lopresti, Pascal Monasse, Hugues Talbot. 
 - 1st ed. 2019. 
 - X, 157 p. 172 illus., 61 illus. in color.  online resource. 
 - Image Processing, Computer Vision, Pattern Recognition, and Graphics,  11455  3004-9954 ; .
 - Image Processing, Computer Vision, Pattern Recognition, and Graphics,  11455 .
<br/><br/>Reproducible Research -- Reproducibility -- Pattern Recognition -- Image Processing -- Image Analysis -- Computer Vision -- Digital Geometry -- Semi-supervised Learning -- Shape analysis -- Evaluation Framework -- Document Image Analysis -- Image Denoising -- Robust Image Processing -- Structure from Motion -- Multiple-view Geometry -- Segment Detection -- IPOL. . 
<br/><br/> This book constitutes the thoroughly refereed post-workshop proceedings of the Second International Workshop on Reproducible Research in Pattern Recognition, RRPR 2018, in Beijing, China in August 2018. The 8 revised full papers, presented together 6 short papers, were carefully reviewed and selected from 14 submissions. This year the workshop did focus on Digital Geometry and Mathematical Morphology. The first track 1 on RR Framework was dedicated to the general topics of Reproducible Research in Computer Science with a potential link to Image Processing and Pattern Recognition. In the second track 2 the authors described their works in terms of Reproducible Research. 
<br/><br/><label>ISBN: </label>9783030239879 
<br/><br/><label>Standard No.: </label>10.1007/978-3-030-23987-9  doi 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Pattern recognition systems.<br/>Computer vision.<br/>Software engineering.<br/>Artificial intelligence.<br/>Automated Pattern Recognition.<br/>Computer Vision.<br/>Software Engineering.<br/>Artificial Intelligence.
<br/><br/><label>LC Class. No.: </label>Q337.5 TK7882.P3 
<br/><br/><label>Dewey Class. No.: </label>006.4