Results 101 to 110 of about 9,977 (122)

AI-driven feature recognition of SEM profiles in deep reactive ion etching based on physics-constrained variational autoencoder. [PDF]

Microsyst Nanoeng
Wang F, Yu H, Miao Y, Sun K, Sun Y, Yang H, Li X.   +6 more
europepmc   +1 more source

Brain over muscle: central mechanisms predominate in gait impairment among older adults with type 2 diabetes mellitus. [PDF]

Front Aging Neurosci
Zhou Z, Wang Z, Li G, Zhang H, Chen Z, Xia Y, Wang Y, Hu J.   +7 more
europepmc   +1 more source

A Radar-Based Contactless System for Joint Phonocardiogram Reconstruction and Cardiac State Segmentation Using a Self-Attention 1D U-Net. [PDF]

Sensors (Basel)
Montanari G, Mura M, Di Viesti P, Vignoli E, Guerzoni G, Vitetta GM.   +5 more
europepmc   +1 more source

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Semantic segmentation using stride spatial pyramid pooling and dual attention decoder

Pattern Recognition, 2020
Abstract Semantic segmentation is an end-to-end task that requires both semantic and spatial accuracy. It is important for deep learning-based segmentation methods to effectively utilize the high-level feature map whose semantic information is abundant and the low-level feature map whose spatial information is accurate. However, existing segmentation
Chengli Peng, Jiayi Ma
exaly   +2 more sources

Challenges of Stride Segmentation and Their Implementation for Impaired Gait

2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2018
Stride segmentation represents important but challenging part of the gait analysis. Different methods and sensor systems have been proposed for detection of markers for segmentation of gait sequences. This task is often performed with wearable sensors comprising force sensors and/or inertial sensors.
Mirjana Popovic, Vladimir Kostic
exaly   +4 more sources

A hidden Markov model-based stride segmentation technique applied to equine inertial sensor trunk movement data

Journal of Biomechanics, 2008
Inertial sensors are now sufficiently small and lightweight to be used for the collection of large datasets of both humans and animals. However, processing of these large datasets requires a certain degree of automation to achieve realistic workloads.
Kevin Parsons, Alan Wilson, Thilo Pfau   +2 more
exaly   +3 more sources

MRUNet-3D: A multi-stride residual 3D UNet for lung nodule segmentation

Methods
Obtaining an accurate segmentation of the pulmonary nodules in computed tomography (CT) images is challenging. This is due to: (1) the heterogeneous nature of the lung nodules; (2) comparable visual characteristics between the nodules and their surroundings.
Yi-Ping Phoebe Chen, Hao Gui
exaly   +3 more sources

Stride segmentation of inertial sensor data using statistical methods for different walking activities

Robotica, 2021
AbstractHuman gait data can be collected using inertial measurement units (IMUs). An IMU is an electronic device that uses an accelerometer and gyroscope to capture three-axial linear acceleration and three-axial angular velocity. The data so collected are time series in nature.
Rahul Jain 0016, Vijay Bhaskar Semwal, Praveen Kaushik   +2 more
openaire   +1 more source

Sensor-based Stride Segmentation and Gait Parameter Extraction Using a Hidden Markov Model in Patients with Hereditary Spastic Paraplegia

2024 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES)
Bjoern Eskofier, Martin Regensburger, Arne Küderle   +2 more
exaly   +2 more sources

Strided U-Net Model: Retinal Vessels Segmentation using Dice Loss

2018 Digital Image Computing: Techniques and Applications (DICTA), 2018
Accurate segmentation of vessels is an arduous task in the analysis of medical images, particularly the extraction of vessels from colored retinal fundus images. Many image processing tactics have been implemented for accurate detection of vessels, but many vessels have been dropped.
Toufique Ahmed Soomro, Olaf Hellwich, Ahmed J. Afifi, Manoranjan Paul, Junbin Gao, Lihong Zheng   +5 more
openaire   +2 more sources