AIMC Topic: Neural Networks, Computer

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Robust Adaptive Self-Structuring Neural Network Bounded Target Tracking Control of Underactuated Surface Vessels.

Computational intelligence and neuroscience
This paper studies the target-tracking problem of underactuated surface vessels with model uncertainties and external unknown disturbances. A composite robust adaptive self-structuring neural-network-bounded controller is proposed to improve system p...

DSC-based RBF neural network control for nonlinear time-delay systems with time-varying full state constraints.

ISA transactions
The presented control scheme in this paper aims at stabilizing uncertain time-delayed systems requiring all states to change within the preset time-varying constraints. The controller design framework is based on the backstepping method, drastically ...

Analysis of high-resolution reconstruction of medical images based on deep convolutional neural networks in lung cancer diagnostics.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: To study the diagnostic effect of 64-slice spiral CT and MRI high-resolution images based on deep convolutional neural networks(CNN) in lung cancer.

SERS and advanced chemometrics - Utilization of Siamese neural network for picomolar identification of beta-lactam antibiotics resistance gene fragment.

Analytica chimica acta
The enormous development and expansion of antibiotic-resistant bacterial strains impel the intensive search for new methods for fast and reliable detection of antibiotic susceptibility markers. Here, we combined DNA-targeted surface functionalization...

LightAnomalyNet: A Lightweight Framework for Efficient Abnormal Behavior Detection.

Sensors (Basel, Switzerland)
The continuous development of intelligent video surveillance systems has increased the demand for enhanced vision-based methods of automated detection of anomalies within various behaviors found in video scenes. Several methods have appeared in the l...

The Compact Support Neural Network.

Sensors (Basel, Switzerland)
Neural networks are popular and useful in many fields, but they have the problem of giving high confidence responses for examples that are away from the training data. This makes the neural networks very confident in their prediction while making gro...

Machine Learning and Its Application in Skin Cancer.

International journal of environmental research and public health
Artificial intelligence (AI) has wide applications in healthcare, including dermatology. Machine learning (ML) is a subfield of AI involving statistical models and algorithms that can progressively learn from data to predict the characteristics of ne...

A stroke detection and discrimination framework using broadband microwave scattering on stochastic models with deep learning.

Scientific reports
Stroke poses an immense public health burden and remains among the primary causes of death and disability worldwide. Emergent therapy is often precluded by late or indeterminate times of onset before initial clinical presentation. Rapid, mobile, safe...

Imaging Manifestations and Evaluation of Postoperative Complications of Bone and Joint Infections under Deep Learning.

Journal of healthcare engineering
To explore and evaluate the imaging manifestations of postoperative complications of bone and joint infections based on deep learning, a retrospective study was performed on 40 patients with bone and joint infections in the Department of Orthopedics ...

Score and Correlation Coefficient-Based Feature Selection for Predicting Heart Failure Diagnosis by Using Machine Learning Algorithms.

Computational and mathematical methods in medicine
Cardiovascular disease (CVD) is one of the most common causes of death that kills approximately 17 million people annually. The main reasons behind CVD are myocardial infarction and the failure of the heart to pump blood normally. Doctors could diagn...