Author(s)

E. J. Dean, A. P. Engelbrecht & A. Nicholas

Abstract

Computer aided identification of biological specimens using self-organizing maps E. J. ~ e a n ' , A. P. ~n~elbrecht~ & A. ~icholas~ I Dept of Information Technology, Durban Institute of Technology, SA 2 Computer Science Department, University of Pretoria, SA 3 Botany Department, University of Durban- Westville, SA Abstract It is often necessary or desirable that biological material be identified. However, given that there is an estimated 10 million living organisms on Earth, the identification of biological material can be problematic and consequently the services of a taxonomist specialist are often required. If such an expert is not readily available it is necessary to attempt an identification using an alternative method; but some of the alternative methods available are unsatisfactory or can lead to a wrong identification. One of the most common problems encountered when identifying specimens is that important diagnostic features are often not easily observed, or may even be completely abs

Keywords