A review of unsupervised feature learning and deep learning for time-series modeling
This paper gives a review of the recent developments in deep learning and unsupervised
feature learning for time-series problems. While these techniques have shown promise for …
feature learning for time-series problems. While these techniques have shown promise for …
Review on algorithm design in electronic noses: Challenges, status, and trends
Electronic noses, or e-noses, refer to systems powered by chemical gas sensors, signal
processing, and machine learning algorithms for realizing artificial olfaction. They play a …
processing, and machine learning algorithms for realizing artificial olfaction. They play a …
Context recognition in-the-wild: Unified model for multi-modal sensors and multi-label classification
Automatic recognition of behavioral context (location, activities, body-posture etc.) can serve
health monitoring, aging care, and many other domains. Recognizing context in-the-wild is …
health monitoring, aging care, and many other domains. Recognizing context in-the-wild is …
On the performance of gas sensor arrays in open sampling systems using Inhibitory Support Vector Machines
A Vergara, J Fonollosa, J Mahiques… - Sensors and Actuators B …, 2013 - Elsevier
Chemo-resistive transduction presents practical advantages for capturing the spatio-
temporal and structural organization of chemical compounds dispersed in different human …
temporal and structural organization of chemical compounds dispersed in different human …
Dynamic neural network architectures for on field stochastic calibration of indicative low cost air quality sensing systems
In the last few years, the interest in the development of new pervasive or mobile
implementations of air quality multisensor devices has significantly grown. New application …
implementations of air quality multisensor devices has significantly grown. New application …
Calibrating chemical multisensory devices for real world applications: An in-depth comparison of quantitative machine learning approaches
Chemical multisensor devices need calibration algorithms to estimate gas concentrations.
Their possible adoption as indicative air quality measurements devices poses new …
Their possible adoption as indicative air quality measurements devices poses new …
A deep machine learning method for classifying cyclic time series of biological signals using time-growing neural network
A Gharehbaghi, M Lindén - IEEE transactions on neural …, 2017 - ieeexplore.ieee.org
This paper presents a novel method for learning the cyclic contents of stochastic time series:
the deep time-growing neural network (DTGNN). The DTGNN combines supervised and …
the deep time-growing neural network (DTGNN). The DTGNN combines supervised and …
Classifiers with a reject option for early time-series classification
N Hatami, C Chira - 2013 IEEE symposium on computational …, 2013 - ieeexplore.ieee.org
Early classification of time-series data in a dynamic environment is a challenging problem of
great importance in signal processing. This paper proposes a classifier architecture with a …
great importance in signal processing. This paper proposes a classifier architecture with a …
A bioinspired neural network for data processing in an electronic nose
YQ Jing, QH Meng, PF Qi, ML Cao… - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
A novel bioinspired neural network is proposed as a replacement for traditional data
processing methods in the electronic nose (e-nose) that we designed. This neural network …
processing methods in the electronic nose (e-nose) that we designed. This neural network …
Pattern recognition for selective odor detection with gas sensor arrays
This paper presents a new pattern recognition approach for enhancing the selectivity of gas
sensor arrays for clustering intelligent odor detection. The aim of this approach was to …
sensor arrays for clustering intelligent odor detection. The aim of this approach was to …