AIMC Topic: Algorithms

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Active Disturbance Rejection Control for an automotive suspension system based on parameter tuning using a fuzzy technique.

PloS one
Road surface roughness is the cause of vehicle vibration, which is considered a system disturbance. Previous studies on suspension system control often ignore the influence of disturbances while designing the controller, leading to system performance...

An ensemble deep learning framework for energy demand forecasting using genetic algorithm-based feature selection.

PloS one
Accurate energy demand forecasting is critical for efficient energy management and planning. Recent advancements in computing power and the availability of large datasets have fueled the development of machine learning models. However, selecting the ...

A Deep and Interpretable Learning Approach for Long-Term ECG Clinical Noise Classification.

IEEE transactions on bio-medical engineering
OBJECTIVE: In Long-Term Monitoring (LTM), noise significantly impacts the quality of the electrocardiogram (ECG), posing challenges for accurate diagnosis and time-consuming analysis. The clinical severity of noise refers to the difficulty in interpr...

Generative Adversarial Networks With Radiomics Supervision for Lung Lesion Generation.

IEEE transactions on bio-medical engineering
Data-driven methods for lesion generation are quickly emerging due to the need for realistic imaging targets for image quality assessment and virtual clinical trials. We proposed a generative adversarial network (GAN) architecture for conditional gen...

Robust Path Planning via Learning From Demonstrations for Robotic Catheters in Deformable Environments.

IEEE transactions on bio-medical engineering
OBJECTIVE: Navigation through tortuous and deformable vessels using catheters with limited steering capability underscores the need for reliable path planning. State-of-the-art path planners do not fully account for the deformable nature of the envir...

Computationally Efficient Implicit Training Strategy for Unrolled Networks (IMUNNE): A Preliminary Analysis Using Accelerated Real-Time Cardiac Cine MRI.

IEEE transactions on bio-medical engineering
OBJECTIVE: Highly-undersampled, dynamic MRI reconstruction, particularly in multi-coil scenarios, is a challenging inverse problem. Unrolled networks achieve state-of-the-art performance in MRI reconstruction but suffer from long training times and e...

Deep Network Regularization for Phase-Based Magnetic Resonance Electrical Properties Tomography With Stein's Unbiased Risk Estimator.

IEEE transactions on bio-medical engineering
Magnetic resonance imaging (MRI) can estimate tissue conductivity values using phase-based magnetic resonance electrical properties tomography (MR-EPT). However, this method is prone to noise amplification due to the Laplacian operator's sensitivity....

Supervised Contrastive Learning-Based Domain Generalization Network for Cross-Subject Motor Decoding.

IEEE transactions on bio-medical engineering
Developing an electroencephalogram (EEG)-based motor imagery and motor execution (MI/ME) decoding system that is both highly accurate and calibration-free for cross-subject applications remains challenging due to domain shift problem inherent in such...

Optimizing automated photo identification for population assessments.

Conservation biology : the journal of the Society for Conservation Biology
Several legal acts mandate that management agencies regularly assess biological populations. For species with distinct markings, these assessments can be conducted noninvasively via capture-recapture and photographic identification (photo-ID), which ...

SSIM over MSE: A new perspective for video anomaly detection.

Neural networks : the official journal of the International Neural Network Society
Video anomaly detection plays a crucial role in ensuring public safety. Its goal is to detect abnormal patterns contained in video frames. Most existing models distinguish the anomalies based on the Mean Squared Error (MSE), which is hard to align wi...