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Using artificial neural networks to classify unknown volatile chemicals from the firings of insect olfactory sensory neurons.

, , , and . EMBC, page 2752-2755. IEEE, (2011)

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Multilayer Perceptron Classification of Unknown Volatile Chemicals from the Firing Rates of Insect Olfactory Sensory Neurons and Its Application to Biosensor Design., , , and . Neural Comput., 25 (1): 259-287 (2013)Artificial Neural Network prediction of specific VOCs and blended VOCs for various concentrations from the olfactory receptor firing rates of Drosophila melanogaster., , and . EMBC, page 3232-3235. IEEE, (2014)Predicting odorant chemical class from odorant descriptor values with an assembly of multi-layer perceptrons., , , and . EMBC, page 2756-2759. IEEE, (2011)Using Multilayer Perceptron Computation to Discover Ideal Insect Olfactory Receptor Combinations in the Mosquito and Fruit Fly for an Efficient Electronic Nose., , and . Neural Comput., 27 (1): 171-201 (2015)"Super E-Noses": Multi-layer perceptron classification of volatile odorants from the firing rates of cross-species olfactory receptor arrays., , and . EMBC, page 954-957. IEEE, (2014)Using artificial neural networks to classify unknown volatile chemicals from the firings of insect olfactory sensory neurons., , , and . EMBC, page 2752-2755. IEEE, (2011)Application of artificial neural networks on mosquito Olfactory Receptor Neurons for an olfactory biosensor., , and . EMBC, page 5390-5393. IEEE, (2013)Improving odorant chemical class prediction with multi-layer perceptrons using temporal odorant spike responses from drosophila melanogaster olfactory receptor neurons., , , and . EMBC, page 6393-6396. IEEE, (2016)