In the last years, digital image processing and analysis are used for computer assisted
evaluation of semen quality with therapeutic goals or to estimate its fertility by means of …

We consider images of boar spermatozoa obtained with an optical phase-contrast
microscope. Our goal is to automatically classify single sperm cells as acrosome-intact …

The thesis presents different concepts to improve the performance of LVQ algorithms. One
issue refers to metric learning in LVQ, ie, the optimization of the employed distance measure …

We propose a method for the classification of boar sperm heads based on their intracellular
intensity distributions observed in microscopic images. The image pre-processing comprises …

We present two approaches to extend Robust Soft Learning Vector Quantization (RSLVQ).
This algorithm for nearest prototype classification is derived from an explicit cost function …

Notice of Removal: Fuzzy rule based classification of human spermatozoa | IEEE
Conference Publication | IEEE Xplore Notice of Removal: Fuzzy rule based classification of …

We consider images of boar spermatozoa obtained with an optical phase-contrast
microscope. Our goal is to automatically classify single sperm cells as acrosome-intact …

Prototype-based classification models, and particularly Learning Vector Quantization (LVQ)
frameworks with adaptive metrics, are powerful supervised classification techniques with …

This book contains keynote lectures and full papers presented at the International
Symposium on Computational Modelling of Objects Represented in Images (CompIMAGE) …

Quality assessment of bull sperms is a necessary task to process to increase a fertilization
rate when applying methods of Assisted Reproductive Technology including In Vitro …