AIMC Topic: Video Recording

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SSIM over MSE: A new perspective for video anomaly detection.

Neural networks : the official journal of the International Neural Network Society
Video anomaly detection plays a crucial role in ensuring public safety. Its goal is to detect abnormal patterns contained in video frames. Most existing models distinguish the anomalies based on the Mean Squared Error (MSE), which is hard to align wi...

Reducing reading time and assessing disease in capsule endoscopy videos: A deep learning approach.

International journal of medical informatics
BACKGROUND: The wireless capsule endoscope (CE) is a valuable diagnostic tool in gastroenterology, offering a safe and minimally invasive visualization of the gastrointestinal tract. One of the few drawbacks identified by the gastroenterology communi...

Spiking-PhysFormer: Camera-based remote photoplethysmography with parallel spike-driven transformer.

Neural networks : the official journal of the International Neural Network Society
Artificial neural networks (ANNs) can help camera-based remote photoplethysmography (rPPG) in measuring cardiac activity and physiological signals from facial videos, such as pulse wave, heart rate and respiration rate with better accuracy. However, ...

Human-Centric Transformer for Domain Adaptive Action Recognition.

IEEE transactions on pattern analysis and machine intelligence
We study the domain adaptation task for action recognition, namely domain adaptive action recognition, which aims to effectively transfer action recognition power from a label-sufficient source domain to a label-free target domain. Since actions are ...

Fine-Grained Fidgety Movement Classification Using Active Learning.

IEEE journal of biomedical and health informatics
Typically developing infants, between the corrected age of 9-20 weeks, produce fidgety movements. These movements can be identified with the General Movement Assessment, but their identification requires trained professionals to conduct the assessmen...

AI-assisted digital video analysis reveals changes in gait among three-day event horses during competition.

Journal of equine veterinary science
The value and welfare of performance horses is closely tied to locomotor behaviors, but we lack objective and quantitative measures for these characteristics, and qualitative approaches for assessing gait do not provide measures suitable for large-sc...

A discriminative multi-modal adaptation neural network model for video action recognition.

Neural networks : the official journal of the International Neural Network Society
Research on video-based understanding and learning has attracted widespread interest and has been adopted in various real applications, such as e-healthcare, action recognition, affective computing, to name a few. Amongst them, video-based action rec...

Comparison between AI and human expert performance in acute pain assessment in sheep.

Scientific reports
This study explores the question whether Artificial Intelligence (AI) can outperform human experts in animal pain recognition using sheep as a case study. It uses a dataset of N = 48 sheep undergoing surgery with video recordings taken before (no pai...

SVM directed machine learning classifier for human action recognition network.

Scientific reports
Understanding human behavior and human action recognition are both essential components of effective surveillance video analysis for the purpose of guaranteeing public safety. However, existing approaches such as three-dimensional convolutional neura...