Combustion machine learning: Principles, progress and prospects
Progress in combustion science and engineering has led to the generation of large amounts
of data from large-scale simulations, high-resolution experiments, and sensors. This corpus …
of data from large-scale simulations, high-resolution experiments, and sensors. This corpus …
Deep neural network concepts for background subtraction: A systematic review and comparative evaluation
Conventional neural networks have been demonstrated to be a powerful framework for
background subtraction in video acquired by static cameras. Indeed, the well-known Self …
background subtraction in video acquired by static cameras. Indeed, the well-known Self …
[PDF][PDF] A Robust 3-D Medical Watermarking Based on Wavelet Transform for Data Protection.
X Zhang, W Zhang, W Sun, X Sun… - … Systems Science & …, 2022 - cdn.techscience.cn
In a telemedicine diagnosis system, the emergence of 3D imaging enables doctors to make
clearer judgments, and its accuracy also directly affects doctors' diagnosis of the disease. In …
clearer judgments, and its accuracy also directly affects doctors' diagnosis of the disease. In …
A novel approach to large-scale dynamically weighted directed network representation
A d ynamically w eighted d irected n etwork (DWDN) is frequently encountered in various big
data-related applications like a terminal interaction pattern analysis system (TIPAS) …
data-related applications like a terminal interaction pattern analysis system (TIPAS) …
NeuLFT: A novel approach to nonlinear canonical polyadic decomposition on high-dimensional incomplete tensors
AH igh-D imensional and I ncomplete (HDI) tensor is frequently encountered in a big data-
related application concerning the complex dynamic interactions among numerous entities …
related application concerning the complex dynamic interactions among numerous entities …
Consensus graph learning for multi-view clustering
Multi-view clustering, which exploits the multi-view information to partition data into their
clusters, has attracted intense attention. However, most existing methods directly learn a …
clusters, has attracted intense attention. However, most existing methods directly learn a …
The flexible tensor singular value decomposition and its applications in multisensor signal fusion processing
A tensor, represented as a multidimensional array, has crucial applications in various fields
such as image processing and high-dimensional data mining. This study defines a novel …
such as image processing and high-dimensional data mining. This study defines a novel …
Infrared small target detection based on partial sum of the tensor nuclear norm
L Zhang, Z Peng - Remote Sensing, 2019 - mdpi.com
Excellent performance, real time and strong robustness are three vital requirements for
infrared small target detection. Unfortunately, many current state-of-the-art methods merely …
infrared small target detection. Unfortunately, many current state-of-the-art methods merely …
Enhanced tensor low-rank and sparse representation recovery for incomplete multi-view clustering
Incomplete multi-view clustering (IMVC) has attracted remarkable attention due to the
emergence of multi-view data with missing views in real applications. Recent methods …
emergence of multi-view data with missing views in real applications. Recent methods …
High-order correlation preserved incomplete multi-view subspace clustering
Incomplete multi-view clustering aims to exploit the information of multiple incomplete views
to partition data into their clusters. Existing methods only utilize the pair-wise sample …
to partition data into their clusters. Existing methods only utilize the pair-wise sample …