AIMC Topic: Algorithms

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Rigid motion-resolved prediction using deep learning for real-time parallel-transmission pulse design.

Magnetic resonance in medicine
PURPOSE: Tailored parallel-transmit (pTx) pulses produce uniform excitation profiles at 7 T, but are sensitive to head motion. A potential solution is real-time pulse redesign. A deep learning framework is proposed to estimate pTx distributions foll...

FDA-regulated AI Algorithms: Trends, Strengths, and Gaps of Validation Studies.

Academic radiology
RATIONALE AND OBJECTIVES: To assess key trends, strengths, and gaps in validation studies of the Food and Drug Administration (FDA)-regulated imaging-based artificial intelligence/machine learning (AI/ML) algorithms.

Online machine learning algorithms to optimize performances of complex wireless communication systems.

Mathematical biosciences and engineering : MBE
Data-driven and feedback cycle-based approaches are necessary to optimize the performance of modern complex wireless communication systems. Machine learning technologies can provide solutions for these requirements. This study shows a comprehensive f...

Time Series Classification with InceptionFCN.

Sensors (Basel, Switzerland)
Deep neural networks (DNN) have proven to be efficient in computer vision and data classification with an increasing number of successful applications. Time series classification (TSC) has been one of the challenging problems in data mining in the la...

Research on Video Quality Evaluation of Sparring Motion Based on BPNN Perception.

Computational intelligence and neuroscience
The quality of boxing video is affected by many factors. For example, it needs to be compressed and encoded before transmission. In the process of transmission, it will encounter network conditions such as packet loss and jitter, which will affect th...

Robust Real-Time Traffic Surveillance with Deep Learning.

Computational intelligence and neuroscience
Real-time vehicle monitoring in highways, roads, and streets may provide useful data both for infrastructure planning and for traffic management in general. Even though it is a classic research area in computer vision, advances in neural networks for...

Using Machine Learning to Identify Intravenous Contrast Phases on Computed Tomography.

Computer methods and programs in biomedicine
PURPOSE: The purpose of the present work is to demonstrate the application of machine learning (ML) techniques to automatically identify the presence and physiologic phase of intravenous (IV) contrast in Computed Tomography (CT) scans of the Chest, A...

Design of a rapid diagnostic model for bladder compliance based on real-time intravesical pressure monitoring system.

Computers in biology and medicine
OBJECTIVE: The diagnosis of bladder dysfunction for children depends on the confirmation of abnormal bladder shape and bladder compliance. The existing gold standard needs to conduct voiding cystourethrogram (VCUG) examination and urodynamic studies ...

Non-Linear Regression Models with Vibration Amplitude Optimization Algorithms in a Microturbine.

Sensors (Basel, Switzerland)
Machinery condition monitoring and failure analysis is an engineering problem to pay attention to among all those being studied. Excessive vibration in a rotating system can damage the system and cannot be ignored. One option to prevent vibrations in...

Attention Autoencoder for Generative Latent Representational Learning in Anomaly Detection.

Sensors (Basel, Switzerland)
Today, accurate and automated abnormality diagnosis and identification have become of paramount importance as they are involved in many critical and life-saving scenarios. To accomplish such frontiers, we propose three artificial intelligence models ...