BryoBrain – Introduction
computer program „BryoBrain“ is a “neural classifier”, a program
that allows the determination of all 73 European (incl. Macaronesian)
foliose liverwort genera (Jungermanniales and Haplomitriales) with the
help of “artificial neural networks“ (ANN) using different
morphological and biometric data. The program gives an impression of how
the determination of plants will work in the future and which methods
will replace the dichotomous keys of the “book age”. It works in a
similar way as many programs for OCR, speech-, fingerprint- or
face-recognition, stock market prediction, industrial quality control
and many other things. Neural networks permit the use of chemical or
molecular data and will be very important tools and show their
capability when these data will be generally available for
identification or with image recognition of species.
ANN used in BryoBrain are multilayer perceptrons (MLP) trained with
backpropagation (for explanation see the “Introductions to ANN” on
The objectives for the development of BryoBrain were first to demonstrate that ANN are capable of identifying bryophytes, and second to test how many and which characters are required for their identification. For a few other species groups classification with ANN was already tested. However, to my knowledge BryoBrain is the world’s first independently executable and distributable program for the determination of plants or animals.
networks are capable of learning (and can thus be considered „artificial
intelligence“), although the distributed version of BryoBrain contains
networks that have already been trained to recognize liverwort genera
and the learning capability has been omitted.
to database solutions, ANN have several advantages, especially:
disadvantage is that the development of an ANN solution different inputs
while database solutions simply compare the inputs with the values in
the databasis more time-consuming and the ANN have to re-trained any
time a change is made to the training data or network topology.
to the last version (0,6) the following features have been improved or
added (see also history):
version 0.7 the recognition rate could be increased, this despite the
significantly higher number of genera. This is particularly due to the
better training data, which have been improved in quantity and quality,
as well to improved networks.
current version (0,7) is still a beta version and possesses some
shortcomings. BryoBrain currently classifies >99% of the testing data
correctly. In spite of the high recognition rate you should not expect
the program to classify all specimens correctly, as the overall
variability of many genera is not yet included in the training and
present BryoBrain has some problems with genera possessing small,
variable underleaves. This issue will require a better definition of the
characters in the training data as well as some changes in the network
topology in the next version.
development of BryoBrain will be continued. I’m currently testing if
all North American genera can be included. In addition, neural nets for
other areas (South America) and other species groups are planned. With
every change the nets have to be trained again, which is time-consuming.
Therefore, the development of the program will continue slowly.
uses in the current release 21-31 characters for the recognition of
genera, which must unfortunately still be entered by hand. The data must
be entered completely in order to avoid
mis-classifications, although in some cases the ANN give the
correct result already with a small set of characters. All characters
are preset to the most common conditions. Therefore several characters,
like the presence of ocelli or a vitta, in most cases do not have to be
BryoBrain uses two perianth characters. Since perianths are not always
available, two different networks are included:
net that uses up to 31 characters is somewhat more reliable, but the
differences are small. In order to use all 31 characters, the box „Use
perianth characters“ must be checked.
users asked for a version that requires fewer characters. Therefore, a
net was included that uses only 12 to 14 characters (which are
recognizable with the hand lens) for classifying. This fast test is
somewhat less reliable (recognition rate ~ 94%).
is now completely bilingual (English/German). The language can be
changed with a single mouseclick. It includes an English and German
introduction and description.
BryoBrain has database functionality and can store the entered data in a database. I have added a database with about 100 records giving the species name in the ‘Observation-field’, which are not known to the ANN. Therefore, you can play around, change the data and test the program and observe the behaviour of the ANN without entering your own data. The feel of such a program is very different from the use of a dichotomous key in a book and one has to get used to it. Of course it is also possible add your own records to the database and feed the ANN with it.
0.7 includes some Internet capabilities. The program can start a picture
search with a search engine using the standard web browser and it can
check the BryoBrain homepage to see if a newer version is available.
is a more detailed description of BryoBrain on my homepage (http://www.drehwald.info)
where the program can be downloaded free of charge.
Requires MS Windows® 9x, ME, NT, 2000 or XP.