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Video Recording

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Automated detection of steps in videos of strabismus surgery using deep learning.

BMC ophthalmology
BACKGROUND: Learning to perform strabismus surgery is an essential aspect of ophthalmologists' surgical training. Automated classification strategy for surgical steps can improve the effectiveness of training curricula and the efficient evaluation of...

Video-based assessments of activities of daily living: generating real-world evidence in pediatric rare diseases.

Expert review of pharmacoeconomics & outcomes research
INTRODUCTION: Preserving function and independence to perform activities of daily living (ADL) is critical for patients and carers to manage the burden of care and improve quality of life. In children living with rare diseases, video recording ADLs o...

Basketball technique action recognition using 3D convolutional neural networks.

Scientific reports
This research investigates the recognition of basketball techniques actions through the implementation of three-dimensional (3D) Convolutional Neural Networks (CNNs), aiming to enhance the accurate and automated identification of various actions in b...

VNVC: A Versatile Neural Video Coding Framework for Efficient Human-Machine Vision.

IEEE transactions on pattern analysis and machine intelligence
Almost all digital videos are coded into compact representations before being transmitted. Such compact representations need to be decoded back to pixels before being displayed to humans and - as usual - before being enhanced/analyzed by machine visi...

Prediction of Achilles Tendon Force During Common Motor Tasks From Markerless Video.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Remodeling of the Achilles tendon (AT) is partly driven by its mechanical environment. AT force can be estimated with neuromusculoskeletal (NMSK) modeling; however, the complex experimental setup required to perform the analyses confines use to the l...

Development of UroSAM: A Machine Learning Model to Automatically Identify Kidney Stone Composition from Endoscopic Video.

Journal of endourology
Chemical composition analysis is important in prevention counseling for kidney stone disease. Advances in laser technology have made dusting techniques more prevalent, but this offers no consistent way to collect enough material to send for chemical...

Laparoscopic distal gastrectomy skill evaluation from video: a new artificial intelligence-based instrument identification system.

Scientific reports
The advent of Artificial Intelligence (AI)-based object detection technology has made identification of position coordinates of surgical instruments from videos possible. This study aimed to find kinematic differences by surgical skill level. An AI a...

Deep Learning-Based Nystagmus Detection for BPPV Diagnosis.

Sensors (Basel, Switzerland)
In this study, we propose a deep learning-based nystagmus detection algorithm using video oculography (VOG) data to diagnose benign paroxysmal positional vertigo (BPPV). Various deep learning architectures were utilized to develop and evaluate nystag...

Real-time sports injury monitoring system based on the deep learning algorithm.

BMC medical imaging
In response to the low real-time performance and accuracy of traditional sports injury monitoring, this article conducts research on a real-time injury monitoring system using the SVM model as an example. Video detection is performed to capture human...

Training deep learning based dynamic MR image reconstruction using open-source natural videos.

Scientific reports
To develop and assess a deep learning (DL) pipeline to learn dynamic MR image reconstruction from publicly available natural videos (Inter4K). Learning was performed for a range of DL architectures (VarNet, 3D UNet, FastDVDNet) and corresponding samp...