Using Multilayer Perceptron Computation to Discover Ideal Insect Olfactory Receptor Combinations in the Mosquito and Fruit Fly for an Efficient Electronic Nose | Citedby Results | Neural Computation | MIT Press

Skip to Main Content

Skip Nav Destination

Using Multilayer Perceptron Computation to Discover Ideal Insect Olfactory Receptor Combinations in the Mosquito and Fruit Fly for an Efficient Electronic Nose

Neural Computation (2015) 27 (1): 171–201.

This article has been cited by the following articles in journals that are participating in Crossref Cited-by Linking.

Multi-layer perceptron classification & quantification of neuronal survival in hypoxic-ischemic brain image slices using a novel gradient direction, grey level co-occurrence matrix image training

Saheli Bhattacharya
Laura Bennet
Joanne O. Davidson
Charles P. Unsworth
Nguyen Quoc Khanh Le

PLOS ONE (2022) 17 (12): e0278874.

Insect odorant receptor nanodiscs for sensitive and specific electrochemical detection of odorant compounds

Jamal Ahmed Cheema
Nihan Aydemir
Colm Carraher
Roshan Khadka
Damon Colbert
Harris T. Lin
Andrew Nelson
Andrew Kralicek
Jadranka Travas-Sejdic

Sensors and Actuators B: Chemical (2021) 329: 129243.

Embedding individualized machine learning prediction models for energy efficient VM consolidation within Cloud data centers

Seyedhamid Mashhadi Moghaddam
Michael O’Sullivan
Cameron Walker
Sareh Fotuhi Piraghaj
Charles Peter Unsworth

Future Generation Computer Systems (2020) 106: 221.

Identifying and Predicting the Expenditure Level Characteristics of Car-Sharing Users Based on the Empirical Data

Sustainability (2019) 11 (23): 6689.

Robust Wavelet Stabilized ‘Footprints of Uncertainty’ for Fuzzy System Classifiers to Automatically Detect Sharp Waves in the EEG after Hypoxia Ischemia

Hamid Abbasi
Laura Bennet
Alistair J. Gunn
Charles P. Unsworth

International Journal of Neural Systems (2017) 27 (03): 1650051.