Amanote Research
Register
Sign In
Confidence Measures for Carbon-Nanotube / Liquid Crystals Classifiers
doi 10.1109/cec.2018.8477779
Full Text
Open PDF
Abstract
Available in
full text
Date
July 1, 2018
Authors
E. Vissol-Gaudin
A. Kotsialos
C. Groves
C. Pearson
D.A. Zeze
M.C. Petty
N. Al Moubayed
Publisher
IEEE
Related search
Improving Optimum-Path Forest Learning Using Bag-Of-Classifiers and Confidence Measures
Pattern Analysis and Applications
Computer Vision
Pattern Recognition
Artificial Intelligence
Ionic Liquid Gated Carbon Nanotube Saturable Absorber for Switchable Pulse Generation
Modification of Carbon Nanotube for Synthesis of Titania Nanotube (Tint)-Carbon Nanotube (Cnt) Composite
Journal of Energy, Mechanical, Material and Manufacturing Engineering
Multi-Walled vs. Single-Walled Carbon Nanotube Dispersions in Nematic Liquid Crystals: Comparative Studies of Optical Transmission and Dielectric Properties
Functional Materials
Materials Science
Training a Carbon-Nanotube/Liquid Crystal Data Classifier Using Evolutionary Algorithms
Lecture Notes in Computer Science
Computer Science
Theoretical Computer Science
Contextual Confidence Measures for Continuous Speech Recognition
Ejection Dynamics of a Simple Liquid From Individual Carbon Nanotube Nozzles
Posterior-Based Confidence Measures for Spoken Term Detection
Spectroscopic Study of Double-Walled Carbon Nanotube Functionalization for Preparation of Carbon Nanotube / Epoxy Composites
Carbon
Materials Science
Chemistry
