Application of process tomography to multiphase flow measurement in industrial and biomedical fields: A review
This paper reviews the latest development and emerging technologies on the application of
process tomography to multiphase flow measurement in industrial and biomedical fields. In …
process tomography to multiphase flow measurement in industrial and biomedical fields. In …
Review of selected advances in electrical capacitance volume tomography for multiphase flow monitoring
Electrical Capacitance Volume Tomography (ECVT) has emerged as an attractive
technology for addressing instrumentation requirements in various energy-related …
technology for addressing instrumentation requirements in various energy-related …
Hyperspectral image classification via multiple-feature-based adaptive sparse representation
A multiple-feature-based adaptive sparse representation (MFASR) method is proposed for
the classification of hyperspectral images (HSIs). The proposed method mainly includes the …
the classification of hyperspectral images (HSIs). The proposed method mainly includes the …
MDID: A multiply distorted image database for image quality assessment
W Sun, F Zhou, Q Liao - Pattern Recognition, 2017 - Elsevier
In this paper, we present a new database, the multiply distorted image database (MDID), to
evaluate image quality assessment (IQA) metrics on multiply distorted images. The database …
evaluate image quality assessment (IQA) metrics on multiply distorted images. The database …
A new methodology for identifying arc fault by sparse representation and neural network
Y Wang, F Zhang, S Zhang - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
This paper proposes a sparse representation and fully connected neural network (SRFCNN)
methodology for residential ac series arc fault identification. The SRFCNN method captures …
methodology for residential ac series arc fault identification. The SRFCNN method captures …
Permittivity reconstruction in electrical capacitance tomography based on visual representation of deep neural network
Electrical Capacitance Tomography (ECT) has been developed for many years and made
great progresses. Successful applications of ECT depend on the accuracy and speed of …
great progresses. Successful applications of ECT depend on the accuracy and speed of …
An image reconstruction algorithm for electrical impedance tomography using adaptive group sparsity constraint
Image quality has long been deemed a key challenge for electrical impedance tomography
(EIT). High-quality image is of great significance for improving the qualitative and …
(EIT). High-quality image is of great significance for improving the qualitative and …
Image reconstruction of electrical capacitance tomography based on an efficient sparse Bayesian learning algorithm
L Zhang, L Dai - IEEE Transactions on Instrumentation and …, 2022 - ieeexplore.ieee.org
Image reconstruction is the main research problem of electrical capacitance tomography
(ECT). In this article, a novel ECT image reconstruction algorithm based on an efficient …
(ECT). In this article, a novel ECT image reconstruction algorithm based on an efficient …
Image reconstruction in electrical capacitance tomography based on deep neural networks
Electrical Capacitance Tomography (ECT) image reconstruction has been largely applied
for industrial applications. However, there is still a crucial need to develop a new framework …
for industrial applications. However, there is still a crucial need to develop a new framework …
Image reconstruction using supervised learning in wearable electrical impedance tomography of the thorax
Electrical impedance tomography (EIT) is a non-invasive technique for visualizing the
internal structure of a human body. Capacitively coupled electrical impedance tomography …
internal structure of a human body. Capacitively coupled electrical impedance tomography …