AIMC Topic: Motion

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Hand Gesture Recognition Using Single Patchable Six-Axis Inertial Measurement Unit via Recurrent Neural Networks.

Sensors (Basel, Switzerland)
Recording human gestures from a wearable sensor produces valuable information to implement control gestures or in healthcare services. The wearable sensor is required to be small and easily worn. Advances in miniaturized sensor and materials research...

Quantification of intravoxel incoherent motion with optimized b-values using deep neural network.

Magnetic resonance in medicine
PURPOSE: To develop a framework for quantifying intravoxel incoherent motion (IVIM) parameters, where a neural network for quantification and b-values for diffusion-weighted imaging are simultaneously optimized.

STAC: Spatial-Temporal Attention on Compensation Information for Activity Recognition in FPV.

Sensors (Basel, Switzerland)
Egocentric activity recognition in first-person video (FPV) requires fine-grained matching of the camera wearer's action and the objects being operated. The traditional method used for third-person action recognition does not suffice because of (1) t...

Hierarchical Long Short-Term Concurrent Memory for Human Interaction Recognition.

IEEE transactions on pattern analysis and machine intelligence
In this work, we aim to address the problem of human interaction recognition in videos by exploring the long-term inter-related dynamics among multiple persons. Recently, Long Short-Term Memory (LSTM) has become a popular choice to model individual d...

Repeatability of IVIM biomarkers from diffusion-weighted MRI in head and neck: Bayesian probability versus neural network.

Magnetic resonance in medicine
PURPOSE: The intravoxel incoherent motion (IVIM) model for DWI might provide useful biomarkers for disease management in head and neck cancer. This study compared the repeatability of three IVIM fitting methods to the conventional nonlinear least-squ...

MINARO HD: control and evaluation of a handheld, highly dynamic surgical robot.

International journal of computer assisted radiology and surgery
PURPOSE: Current surgical robotic systems are either large serial arms, resulting in higher risks due to their high inertia and no inherent limitations of the working space, or they are bone-mounted, adding substantial additional task steps to the su...

Development of a Real-Time Human-Robot Collaborative System Based on 1 kHz Visual Feedback Control and Its Application to a Peg-in-Hole Task.

Sensors (Basel, Switzerland)
In this research, we focused on Human-Robot collaboration. There were two goals: (1) to develop and evaluate a real-time Human-Robot collaborative system, and (2) to achieve concrete tasks such as collaborative peg-in-hole using the developed system....

Retrospective motion artifact correction of structural MRI images using deep learning improves the quality of cortical surface reconstructions.

NeuroImage
Head motion during MRI acquisition presents significant challenges for neuroimaging analyses. In this work, we present a retrospective motion correction framework built on a Fourier domain motion simulation model combined with established 3D convolut...

Real-time liver tracking algorithm based on LSTM and SVR networks for use in surface-guided radiation therapy.

Radiation oncology (London, England)
BACKGROUND: Surface-guided radiation therapy can be used to continuously monitor a patient's surface motions during radiotherapy by a non-irradiating, noninvasive optical surface imaging technique. In this study, machine learning methods were applied...

A non-conventional lightweight Auto Regressive Neural Network for accurate and energy efficient target tracking in Wireless Sensor Network.

ISA transactions
The design of an energy-efficient tracking framework is a well-investigated issue and a prominent sensor network application. The current research state shows a clear scope for developing algorithms that can work, accompanying both energy efficiency ...