AIMC Topic: Video Recording

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Fine-Tuning on AI-Driven Video Analysis through Machine Learning: Development of an Automated Evaluation Tool of Facial Palsy.

Plastic and reconstructive surgery
BACKGROUND: Establishment of a quantitative, objective evaluation tool for facial palsy has been a challenging issue for clinicians and researchers, and artificial intelligence-driven video analysis can be considered a reasonable solution. The author...

SurgiTrack: Fine-grained multi-class multi-tool tracking in surgical videos.

Medical image analysis
Accurate tool tracking is essential for the success of computer-assisted intervention. Previous efforts often modeled tool trajectories rigidly, overlooking the dynamic nature of surgical procedures, especially tracking scenarios like out-of-body and...

Enhancing space-time video super-resolution via spatial-temporal feature interaction.

Neural networks : the official journal of the International Neural Network Society
The target of space-time video super-resolution (STVSR) is to increase both the frame rate (also referred to as the temporal resolution) and the spatial resolution of a given video. Recent approaches solve STVSR using end-to-end deep neural networks....

TSFF-Net: A deep fake video detection model based on two-stream feature domain fusion.

PloS one
With the advancement of deep forgery techniques, particularly propelled by generative adversarial networks (GANs), identifying deepfake faces has become increasingly challenging. Although existing forgery detection methods can identify tampering deta...

Semantically-Enhanced Feature Extraction with CLIP and Transformer Networks for Driver Fatigue Detection.

Sensors (Basel, Switzerland)
Drowsy driving is a leading cause of commercial vehicle traffic crashes. The trend is to train fatigue detection models using deep neural networks on driver video data, but challenges remain in coarse and incomplete high-level feature extraction and ...

A multi-memory-augmented network with a curvy metric method for video anomaly detection.

Neural networks : the official journal of the International Neural Network Society
Anomaly detection task in video mainly refers to identifying anomalous events that do not conform to the learned normal patterns in the inferring phase. However, the Euclidean metric used in the learning and inferring phase by the most of the existin...

Identifying Infant Body Position from Inertial Sensors with Machine Learning: Which Parameters Matter?

Sensors (Basel, Switzerland)
The efficient classification of body position is crucial for monitoring infants' motor development. It may fast-track the early detection of developmental issues related not only to the acquisition of motor milestones but also to postural stability a...

Self-Supervised Cyclic Diffeomorphic Mapping for Soft Tissue Deformation Recovery in Robotic Surgery Scenes.

IEEE transactions on medical imaging
The ability to recover tissue deformation from surgical video is fundamental for many downstream applications in robotic surgery. Despite noticeable advancements, this task remains under-explored due to the complex dynamics of soft tissues manipulate...

Research on machine vision online monitoring system for egg production and quality in cage environment.

Poultry science
In the domain of egg production, the application of automation technologies is essential for boosting productivity and quality. This study introduces an online monitoring system designed for egg quality assessment within caged environments, incorpora...

Effectiveness of Comprehensive Video Datasets: Toward the Development of an Artificial Intelligence Model for Ultrasonography-Based Severity Diagnosis of Carpal Tunnel Syndrome.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
OBJECTIVES: Advances in diagnosing carpal tunnel syndrome (CTS) using ultrasonography (US) and artificial intelligence (AI) aim to replace nerve conduction studies. However, a method for accurate severity diagnosis remains unachieved. We explored the...