0000000000520661

AUTHOR

Santiago Velasco-forero

0000-0002-2438-1747

showing 2 related works from this author

SHREC 2020: Retrieval of digital surfaces with similar geometric reliefs

2020

Abstract This paper presents the methods that have participated in the SHREC’20 contest on retrieval of surface patches with similar geometric reliefs and the analysis of their performance over the benchmark created for this challenge. The goal of the context is to verify the possibility of retrieving 3D models only based on the reliefs that are present on their surface and to compare methods that are suitable for this task. This problem is related to many real world applications, such as the classification of cultural heritage goods or the analysis of different materials. To address this challenge, it is necessary to characterize the local ”geometric pattern” information, possibly forgetti…

Information retrievalForgettingGeometric patternComputer scienceGeneral Engineering020207 software engineering3d modelContext (language use)02 engineering and technologyCONTESTComputer Graphics and Computer-Aided DesignTask (project management)Human-Computer InteractionCultural heritageBenchmark (surveying)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputers & Graphics
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Manipulating the alpha level cannot cure significance testing

2018

We argue that making accept/reject decisions on scientific hypotheses, including a recent call for changing the canonical alpha level from p = 0.05 to p = 0.005, is deleterious for the finding of new discoveries and the progress of science. Given that blanket and variable alpha levels both are problematic, it is sensible to dispense with significance testing altogether. There are alternatives that address study design and sample size much more directly than significance testing does; but none of the statistical tools should be taken as the new magic method giving clear-cut mechanical answers. Inference should not be based on single studies at all, but on cumulative evidence from multiple in…

P-VALUENULL HYPOTHESIS TESTINGInference[INFO.INFO-DM]Computer Science [cs]/Discrete Mathematics [cs.DM][INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]0302 clinical medicineddc:150[STAT.ML]Statistics [stat]/Machine Learning [stat.ML]EconometricsPsychologyConceptual AnalysisPsychology(all)General Psychology//purl.org/becyt/ford/5.1 [https][STAT.AP]Statistics [stat]/Applications [stat.AP]//purl.org/becyt/ford/5 [https]05 social sciences050301 educationBayes factorStatistical significanceJustice and Strong InstitutionsVariable (computer science)Alpha (programming language)[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]PsychologySignificance testing[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingNull hypothesis testingSDG 16 - PeaceSIGNIFICANCE TESTINGlcsh:BF1-990Presa de decisions (Estadística)Statistical decision050105 experimental psychologyTests d'hipòtesi (Estadística)CIENCIAS SOCIALESStatistical hypothesis testing03 medical and health sciences0502 economics and business0501 psychology and cognitive sciencesp-valueSTATISTICAL SIGNIFICANCEDECISION MAKINGBinary decision diagramSDG 16 - Peace Justice and Strong InstitutionsMagic (programming)/dk/atira/pure/sustainabledevelopmentgoals/peace_justice_and_strong_institutionsPsicologíaP-valuelcsh:PsychologySample size determination0503 educationDecision making030217 neurology & neurosurgery050203 business & management
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