In sensor-related subjects, sensor drift is an urgent and challenging problem because of its
negative impact on the recognition performance and long-term detection of sensors. Earlier …

An electronic nose (EN) is a bionic system that relies on an array of gas sensors for effective
odor recognition. Since the gas-sensor drift would depress the EN performance, we …

Gas sensor drift is a critical problem in E-nose since it negatively affects recognition
performance. Domain adaptation is currently an advanced method widely used for sensor …

The gas sensor drift problem arises from the bias of data, which is known as a significant
problem in the artificial olfactory community. Traditionally, hardware calibration methods are …

Sensor drift is one of the severe issues that gas sensors suffer from. To alleviate the sensor
drift problem, a gas sensor drift compensation approach is proposed based on local …

Sensor drift is an important problem for biologically inspired Electronic Nose (E-Nose) in
industrial cyber-physical systems and their related applications, as it will deteriorate the …

Domain adaptation, a type of transfer learning, has been theoretically adopted to the
electronic nose (EN) drift problem. Current academic achievements in this field are inspired …

The long-term sensor drift phenomenon seriously restricts the performance of Electronic
Nose (E-nose) systems in their various applications. Due to frequent recalibrations …

The drift caused by gas sensors has always been a bottleneck in the development of
electronic nose (E-nose) systems. Traditional drift compensation methods directly correct the …

This article presents a novel discriminative subspace-learning-based unsupervised domain
adaptation (DA) method for the gas sensor drift problem. Many existing subspace learning …