A review on machine learning styles in computer vision—techniques and future directions

SV Mahadevkar, B Khemani, S Patil, K Kotecha… - Ieee …, 2022 - ieeexplore.ieee.org
Computer applications have considerably shifted from single data processing to machine
learning in recent years due to the accessibility and availability of massive volumes of data …

Multi-fault diagnosis of Industrial Rotating Machines using Data-driven approach: A review of two decades of research

S Gawde, S Patil, S Kumar, P Kamat, K Kotecha… - … Applications of Artificial …, 2023 - Elsevier
Industry 4.0 is an era of smart manufacturing. Manufacturing is impossible without the use of
machinery. The majority of these machines comprise rotating components and are called …

A few shot classification methods based on multiscale relational networks

W Zheng, X Tian, B Yang, S Liu, Y Ding, J Tian, L Yin - Applied Sciences, 2022 - mdpi.com
Learning information from a single or a few samples is called few-shot learning. This
learning method will solve deep learning's dependence on a large sample. Deep learning …

Augmented data driven self-attention deep learning method for imbalanced fault diagnosis of the HVAC chiller

C Shen, H Zhang, S Meng, C Li - Engineering Applications of Artificial …, 2023 - Elsevier
The chiller fault diagnosis is of great significance to maintain the normal operation of the
HVAC system and indoor comfort. Due to the difficulty in collecting the chiller's fault data, we …

TL–LEDarcNet: Transfer Learning Method for Low-Energy Series DC Arc-Fault Detection in Photovoltaic Systems

Y Sung, G Yoon, JH Bae, S Chae - IEEE Access, 2022 - ieeexplore.ieee.org
The arc-fault phenomenon in photovoltaic (PV) systems has emerged as a major problem in
recent years. Existing studies on arc-fault detection in conventional PV systems primarily …

Multi-sensor GA-BP algorithm based gearbox fault diagnosis

Y Fu, Y Liu, Y Yang - Applied Sciences, 2022 - mdpi.com
To address the problem of the low recognition rate of time-frequency domain methods
gearbox fault identification, a method featuring decision-level fusion of DS evidence theory …

A Framework for Multivariate Statistical Quality Monitoring of Additive Manufacturing: Fused Filament Fabrication Process

M Alatefi, AM Al-Ahmari, AY AlFaify, M Saleh - Processes, 2023 - mdpi.com
Advances in additive manufacturing (AM) processes have increased the number of relevant
applications in various industries. To keep up with this development, the process stability of …

A motor bearing fault diagnosis method based on multi-source data and one-dimensional lightweight convolution neural network

Y Dong, C Wen, Z Wang - … , Part I: Journal of Systems and …, 2023 - journals.sagepub.com
Deep learning is widely adopted in the field of fault diagnosis because of its powerful feature
representation capabilities. The existing diagnosis methods are always proposed based on …

Empirical analysis of sensor type importance for data preparation of real-time operational status monitoring in fused deposition modeling 3D printers

S Baek, BS Kim, Y Lee - The International Journal of Advanced …, 2024 - Springer
The fused deposition modeling (FDM)-type three-dimensional (3D) printer is a popular
choice in manufacturing facilities due to its capability of printing complex-shaped objects …

[HTML][HTML] EmerSense: A low-cost multiparameter logger to monitor occurrence and duration of emersion events within intertidal zones

RC Poquita-Du, IPM Du, PA Todd - HardwareX, 2023 - Elsevier
The intertidal zone is a harsh environment for marine life as conditions are often both
extreme and variable. A wide range of sessile organisms are partially or fully emersed …