This study deals with the application of a machine learning algorithm (a classification tree) to assess the weight ofCorallium rubrum(Cnidaria, Octocorallia) ramifications on the basis of the number of apices. Our approach can be easily applied to obtainin situestimates of weight and basal diameter of colonies. Future developments include the integration with image acquisition and processing hardware.
A Machine learning approach to the study of a red coralCorallium rubrum(l.) population = Un'Applicazione del machine learning per lo studio di una popolazione di corallo rossoCorallium rubrum(L.) / Chessa, Lorenzo Antonio; Scardi, Michele. - In: BIOLOGIA MARINA MEDITERRANEA. - ISSN 1123-4245. - 17:1(2010), pp. 109-111.
A Machine learning approach to the study of a red coralCorallium rubrum(l.) population = Un'Applicazione del machine learning per lo studio di una popolazione di corallo rossoCorallium rubrum(L.)
Chessa, Lorenzo Antonio;
2010-01-01
Abstract
This study deals with the application of a machine learning algorithm (a classification tree) to assess the weight ofCorallium rubrum(Cnidaria, Octocorallia) ramifications on the basis of the number of apices. Our approach can be easily applied to obtainin situestimates of weight and basal diameter of colonies. Future developments include the integration with image acquisition and processing hardware.| File | Dimensione | Formato | |
|---|---|---|---|
|
Chessa_L_machine_learning_approach_to.pdf
accesso aperto
Tipologia:
Versione editoriale (versione finale pubblicata)
Licenza:
Non specificato
Dimensione
154.65 kB
Formato
Adobe PDF
|
154.65 kB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
