Image analysis, neural networks, and the taxonomic impediment to biodiversity studies

The taxonomic impediment to biodiversity studies may be influenced radically by the application of new technology, in particular, desktop image analysers and neural networks. The former offer an opportunity to automate objective feature measurement processes, and the latter provide powerful pattern recognition and data analysis tools which are able to 'learn' patterns in multivariate data. The coupling of these technologies may provide a realistic opportunity for the automation of routine species identifications. The potential benefits and limitations of these technologies, along with the development of automated identification systems are reviewed.

[1]  H. Townes,et al.  Ichneumon-flies of America North of Mexico pt. 2: Subfamilies Ephialtinae, Xoridinae, and Acaenitinae , 1960 .

[2]  Martin H. Smith.  Information processing in neural networks , 1977 .

[3]  Tracy Allen,et al.  Computer-Assisted Measurement and Identification of Honey Bees (Hymenoptera: Apidae) , 1982 .

[4]  F. James Rohlf,et al.  Automatic Description of the Venation of Mosquito Wings from Digitized Images , 1985 .

[5]  Makoto Omori,et al.  The identification, counting, and measurement of phytoplankton by an image-processing system , 1987 .

[6]  Teuvo Kohonen,et al.  Self-Organization and Associative Memory , 1988 .

[7]  G. R. Platner,et al.  Phenotypic plasticity and taxonomic characters in Trichogramma (Hymenoptera: Trichogrammatidae) , 1989 .

[8]  Francis Crick,et al.  The recent excitement about neural networks , 1989, Nature.

[9]  Kenneth W. Estep,et al.  Counting, sizing, and identification of algae using image analysis , 1989 .

[10]  Ciamac C. Moallemi,et al.  Classifying cells for cancer diagnosis using neural networks , 1991, IEEE Expert.

[11]  Richard Lippmann,et al.  Neural Network Classifiers Estimate Bayesian a posteriori Probabilities , 1991, Neural Computation.

[12]  R. Gámez.  Biodiversity Conservation through facilitation of its sustainable use: Costa Rica's National Biodiversity Institute. , 1991, Trends in ecology & evolution.

[13]  C. T. Morrow,et al.  Neural networks versus traditional classifiers for machine vision inspection , 1991 .

[14]  Riccardo Poli,et al.  A neural network expert system for diagnosing and treating hypertension , 1991, Computer.

[15]  G. B. Schaalje,et al.  Identification of ichneumonid wasps using image analysis of wings , 1992 .

[16]  Kevin J. Gaston,et al.  Taxonomy of taxonomists , 1992, Nature.

[17]  Gerrit Polder,et al.  Identification of Mushroom Cultivars Using Image Analysis , 1992 .

[18]  A. I. Galushkin,et al.  Neural network expert system , 1992, [Proceedings] 1992 RNNS/IEEE Symposium on Neuroinformatics and Neurocomputers.

[19]  P. Cranston,et al.  Rapid Assessment of Biodiversity using 'Biological Diversity Technicians' , 1992 .

[20]  K. Gaston,et al.  Spatial patterns in the description and richness of the Hymenoptera. , 1993 .

[21]  Lynne Boddy,et al.  Neural Network Analysis of Flow Cytometry Data , 1993 .

[22]  P. Alberch.  Museums, collections and biodiversity inventories. , 1993, Trends in ecology & evolution.

[23]  Anil K. Jain,et al.  Segmentation and classification of bacterial culture images , 1994 .

[24]  G. Kane.  Parallel Distributed Processing: Explorations in the Microstructure of Cognition, vol 1: Foundations, vol 2: Psychological and Biological Models , 1994 .

[25]  D. M. Titterington,et al.  Neural Networks: A Review from a Statistical Perspective , 1994 .

[26]  Charles M. Bachmann,et al.  Neural Networks and Their Applications , 1994 .

[27]  J Morris,et al.  Neural-network contributions in biotechnology. , 1994, Trends in biotechnology.

[28]  C. W. Morris,et al.  Neural network analysis of flow cytometric data for 40 marine phytoplankton species. , 1994, Cytometry.

[29]  Christopher H. Dietrich,et al.  Automated identification of leafhoppers (Homoptera: Cicadellidae: Draeculacephala Ball) , 1994 .

[30]  Alice J. O'Toole,et al.  Connectionist models of face processing: A survey , 1994, Pattern Recognit..

[31]  M. Edwards,et al.  The potential for computer-aided identification in biodiversity research. , 1995, Trends in ecology & evolution.

[32]  Irene Gargantini,et al.  Computer-based image analysis for the automated counting and morphological description of microalgae in culture , 1989, Journal of Applied Phycology.

[33]  Mar Ecol Ser Prog,et al.  Biological pattern recognition by neural networks , .