0000000000590484

AUTHOR

Paul Wilkin

0000-0003-4982-7175

showing 3 related works from this author

Late Cretaceous-Early Eocene origin of yams (Dioscorea, Dioscoreaceae) in the Laurasian Palaearctic and their subsequent Oligocene-Miocene diversific…

2015

Aim: Dioscorea (Dioscoreaceae) is a predominantly pantropical genus (< 600 species) that includes the third most important tropical tuber crop and species of pharmacological value. Fossil records from both the Northern and Southern Hemispheres were used to test hypotheses about the origin of the genus Dioscorea, and to examine potential macroevolutionary processes that led to its current distribution. Location: Pantropical distribution. Methods: Divergence times were estimated using the most comprehensive phylogeny of the group published to date based on plastid sequences and fossil calibrations, applying a relaxed-clock model approach. Ancestral areas and range shifts were reconstructed us…

0106 biological sciencesRange (biology)Thulean – Beringian land bridgesBiogeographyDispersal-extinction-cladogenesis modelPantropicalBiologySoutheast asianN-S American Long-Distance Dispersal010603 evolutionary biology01 natural sciencesPalaearctic – Nearctic colonizationPaleontologyLaurasian originEcology Evolution Behavior and SystematicsEcologyEcologyLand bridgePantropical distributionFossil constrainsWestern Palaearcticbiology.organism_classificationYamsPhylogenetic datingBiogeographyBiological dispersalDioscorea010606 plant biology & botany
researchProduct

A nuclear Xdh phylogenetic analysis of yams (Dioscorea: Dioscoreaceae) congruent with plastid trees reveals a new Neotropical lineage

2018

0301 basic medicine03 medical and health sciences030104 developmental biologybiologyPhylogenetic treeEvolutionary biologyDioscoreaceaeLineage (evolution)DioscoreaPlant SciencePlastidbiology.organism_classificationEcology Evolution Behavior and SystematicsBotanical Journal of the Linnean Society
researchProduct

Reverse engineering expert visual observations: From fixations to the learning of spatial filters with a neural-gas algorithm

2013

Human beings can become experts in performing specific vision tasks, for example, doctors analysing medical images, or botanists studying leaves. With sufficient knowledge and experience, people can become very efficient at such tasks. When attempting to perform these tasks with a machine vision system, it would be highly beneficial to be able to replicate the process which the expert undergoes. Advances in eye-tracking technology can provide data to allow us to discover the manner in which an expert studies an image. This paper presents a first step towards utilizing these data for computer vision purposes. A growing-neural-gas algorithm is used to learn a set of Gabor filters which give h…

Reverse engineeringNeural gasComputer sciencebusiness.industryProcess (engineering)ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONGeneral Engineeringcomputer.software_genreMachine learningComputer Science ApplicationsTask (project management)Image (mathematics)Artificial IntelligenceEye trackingArtificial intelligenceSet (psychology)businesscomputerAlgorithmExpert Systems with Applications
researchProduct