Towards semen quality assessment using neural networks

The paper presents the methodology and results from a neural net based classification of human sperm head morphology. The methodology uses a preprocessing scheme in which invariant Fourier descriptors are lumped into "energy" bands. The resulting networks are pruned using optimal brain damage. Performance comparable to the error rate for human technicians is obtained.<
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