Deep learning on medical image analysis

J Wang, S Wang, Y Zhang - CAAI Transactions on Intelligence …, 2024‏ - Wiley Online Library
Medical image analysis plays an irreplaceable role in diagnosing, treating, and monitoring
various diseases. Convolutional neural networks (CNNs) have become popular as they can …

Exploring multiple instance learning (MIL): A brief survey

M Waqas, SU Ahmed, MA Tahir, J Wu… - Expert Systems with …, 2024‏ - Elsevier
Abstract Multiple Instance Learning (MIL) is a learning paradigm, where training instances
are arranged in sets, called bags, and only bag-level labels are available during training …

DPMSN: A dual-pathway multiscale network for image forgery detection

N Zeng, P Wu, Y Zhang, H Li, J Mao… - IEEE Transactions on …, 2024‏ - ieeexplore.ieee.org
Multimedia images have become an important way for the sharing of digital information.
However, advanced editing tools provide easy methods for malicious content modification …

Bearing fault diagnosis via fusing small samples and training multi-state Siamese neural networks

C Wen, Y Xue, W Liu, G Chen, X Liu - Neurocomputing, 2024‏ - Elsevier
Recently, deep learning techniques have been widely applied to fault diagnosis due to their
outstanding feature extraction abilities. The success of deep-learning-based fault diagnosis …

A novel local binary temporal convolutional neural network for bearing fault diagnosis

Y Xue, R Yang, X Chen, Z Tian… - IEEE Transactions on …, 2023‏ - ieeexplore.ieee.org
In bearing fault diagnosis, the faulty data are generally limited due to the high cost of fault
signal collection. Considering the excessive parameters in the traditional convolutional …

A deep learning approach for electric motor fault diagnosis based on modified InceptionV3

L Xu, SS Teoh, H Ibrahim - Scientific Reports, 2024‏ - nature.com
Electric motors are essential equipment widely employed in various sectors. However,
factors such as prolonged operation, environmental conditions, and inadequate …

[HTML][HTML] Enhancing the super-resolution of medical images: Introducing the deep residual feature distillation channel attention network for optimized performance and …

S Umirzakova, S Mardieva, S Muksimova, S Ahmad… - Bioengineering, 2023‏ - mdpi.com
In the advancement of medical image super-resolution (SR), the Deep Residual Feature
Distillation Channel Attention Network (DRFDCAN) marks a significant step forward. This …

A survey on privacy-preserving control and filtering of networked control systems

W Wang, L Ma, Q Rui, C Gao - International Journal of Systems …, 2024‏ - Taylor & Francis
With the increasing utilisation of information technology and artificial intelligence in practical
control systems, particularly in large-scale distributed networked systems, growing concerns …

One model to unite them all: Personalized federated learning of multi-contrast MRI synthesis

O Dalmaz, MU Mirza, G Elmas, M Ozbey, SUH Dar… - Medical Image …, 2024‏ - Elsevier
Curation of large, diverse MRI datasets via multi-institutional collaborations can help
improve learning of generalizable synthesis models that reliably translate source-onto target …

Zonotope-based distributed set-membership fusion estimation for artificial neural networks under the dynamic event-triggered mechanism

Z Zhao, Z Wang, L Zou, H Liu… - IEEE Transactions on …, 2023‏ - ieeexplore.ieee.org
This article is concerned with the distributed set-membership fusion estimation problem for a
class of artificial neural networks (ANNs), where the dynamic event-triggered mechanism …