AIMC Topic: Acceleration

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MEDL-Net: A model-based neural network for MRI reconstruction with enhanced deep learned regularizers.

Magnetic resonance in medicine Jan 19, 2023
PURPOSE: To improve the MRI reconstruction performance of model-based networks and to alleviate their large demand for GPU memory.
Neural Networks, Computer Algorithms Image Processing, Computer-Assisted Magnetic Resonance Imaging Acceleration
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Novel Deep Learning Network for Gait Recognition Using Multimodal Inertial Sensors.

Sensors (Basel, Switzerland) Jan 11, 2023
Some recent studies use a convolutional neural network (CNN) or long short-term memory (LSTM) to extract gait features, but the methods based on the CNN and LSTM have a high loss rate of time-series and spatial information, respectively. Since gait h...
Neural Networks, Computer Deep Learning Gait Acceleration
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Acceleration of knee magnetic resonance imaging using a combination of compressed sensing and commercially available deep learning reconstruction: a preliminary study.

BMC medical imaging Jan 9, 2023
PURPOSE: To evaluate whether deep learning reconstruction (DLR) accelerates the acquisition of 1.5-T magnetic resonance imaging (MRI) knee data without image deterioration.
Humans Deep Learning Magnetic Resonance Imaging Knee Joint Acceleration Signal-To-Noise Ratio
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Hyperspectral Imaging for Mobile Robot Navigation.

Sensors (Basel, Switzerland) Dec 29, 2022
The article presents the application of a hyperspectral camera in mobile robot navigation. Hyperspectral cameras are imaging systems that can capture a wide range of electromagnetic spectra. This feature allows them to detect a broader range of color...
Neural Networks, Computer Algorithms Robotics Acceleration Hyperspectral Imaging
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Control Strategy of an Underactuated Underwater Drone-Shape Robot for Grasping Tasks.

Sensors (Basel, Switzerland) Nov 15, 2022
In underwater environments, ensuring people's safety is complicated, with potentially life-threatening outcomes, especially when divers have to work in deeper conditions. To improve the available solutions for working with robots in this kind of envi...
Humans Feedback Robotics Acceleration Hydrodynamics Unmanned Aerial Devices
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Acceleration of Deep Neural Network Training Using Field Programmable Gate Arrays.

Computational intelligence and neuroscience Oct 17, 2022
Convolutional neural network (CNN) training often necessitates a considerable amount of computational resources. In recent years, several studies have proposed for CNN inference and training accelerators in which the FPGAs have previously demonstrate...
Neural Networks, Computer Algorithms Acceleration
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A densely interconnected network for deep learning accelerated MRI.

Magma (New York, N.Y.) Sep 14, 2022
OBJECTIVE: To improve accelerated MRI reconstruction through a densely connected cascading deep learning reconstruction framework.
Deep Learning Magnetic Resonance Imaging Acceleration Signal-To-Noise Ratio
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Fall-from-Height Detection Using Deep Learning Based on IMU Sensor Data for Accident Prevention at Construction Sites.

Sensors (Basel, Switzerland) Aug 16, 2022
Workers at construction sites are prone to fall-from-height (FFH) accidents. The severity of injury can be represented by the acceleration peak value. In the study, a risk prediction against FFH was made using IMU sensor data for accident prevention ...
Humans Male Deep Learning Acceleration Movement Accident Prevention
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Toward Full-Stack Acceleration of Deep Convolutional Neural Networks on FPGAs.

IEEE transactions on neural networks and learning systems Aug 3, 2022
Due to the huge success and rapid development of convolutional neural networks (CNNs), there is a growing demand for hardware accelerators that accommodate a variety of CNNs to improve their inference latency and energy efficiency, in order to enable...
Neural Networks, Computer Algorithms Computers Signal Processing, Computer-Assisted Acceleration
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Early Termination Based Training Acceleration for an Energy-Efficient SNN Processor Design.

IEEE transactions on biomedical circuits and systems Jul 12, 2022
In this paper, we present a novel early termination based training acceleration technique for temporal coding based spiking neural network (SNN) processor design. The proposed early termination scheme can efficiently identify the non-contributing tra...
Neural Networks, Computer Computers Acceleration
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