Hybrid electronic tongue based on multisensor data fusion for discrimination of beers

JM Gutiérrez, Z Haddi, A Amari, B Bouchikhi… - Sensors and Actuators B …, 2013 - Elsevier
This paper reports the use of a hybrid electronic tongue based on data fusion of two different
sensor families, applied in the recognition of beer types. Six modified graphite-epoxy …

Convolutional neural network on three orthogonal planes for dynamic texture classification

V Andrearczyk, PF Whelan - Pattern Recognition, 2018 - Elsevier
Abstract Dynamic Textures (DTs) are sequences of images of moving scenes that exhibit
certain stationarity properties in time such as smoke, vegetation and fire. The analysis of DT …

Batch-to-batch optimal control of a batch polymerisation process based on stacked neural network models

J Zhang - Chemical Engineering Science, 2008 - Elsevier
A neural network based batch-to-batch optimal control strategy is proposed in this paper. In
order to overcome the difficulty in develo** mechanistic models for batch processes …

A new Correlation-Similarity Conjoint Algorithm for develo** Encoder-Decoder based deep learning multi-step prediction model of chemical process

Y Li, H Cao, X Wang, Z Yang, N Li, W Shen - Chemical Engineering …, 2024 - Elsevier
As an important procedure for the multi-step modeling of chemical process, the feature
selection approach for unequal-length process variable series is frequently studied based …

LBVCNN: Local binary volume convolutional neural network for facial expression recognition from image sequences

S Kumawat, M Verma, S Raman - Proceedings of the IEEE …, 2019 - openaccess.thecvf.com
Recognizing facial expressions is one of the central problems in computer vision. Temporal
image sequences have useful spatio-temporal features for recognizing expressions. In this …

Modelling of a post-combustion CO2 capture process using neural networks

F Li, J Zhang, E Oko, M Wang - Fuel, 2015 - Elsevier
This paper presents a study of modelling post-combustion CO 2 capture process using
bootstrap aggregated neural networks. The neural network models predict CO 2 capture rate …

[책][B] Data fusion mathematics: theory and practice

JR Raol - 2015 - books.google.com
In a focused, in-depth study, this book explores the mathematical tools used in this
increasingly widespread and important technical field. It includes the theory, methods, and …

Multiple neural networks modeling techniques in process control: a review

Z Ahmad, RA Mat Noor, J Zhang - Asia‐Pacific Journal of …, 2009 - Wiley Online Library
This paper reviews new techniques to improve neural network model robustness for
nonlinear process modeling and control. The focus is on multiple neural networks. Single …

Genetic algorithms based optimization of artificial neural network architecture for buildings' indoor discomfort and energy consumption prediction

F Boithias, M El Mankibi, P Michel - Building Simulation, 2012 - Springer
Growing concerns about energy consumption reduction and comfort improvement inside
buildings make it more and more necessary to be able to predict with fine precision …

A reliable multi-objective control strategy for batch processes based on bootstrap aggregated neural network models

A Mukherjee, J Zhang - Journal of Process Control, 2008 - Elsevier
This paper presents a reliable multi-objective optimal control method for batch processes
based on bootstrap aggregated neural networks. In order to overcome the difficulty in …