AIMC Topic: Video Recording

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Selfee, self-supervised features extraction of animal behaviors.

eLife
Fast and accurately characterizing animal behaviors is crucial for neuroscience research. Deep learning models are efficiently used in laboratories for behavior analysis. However, it has not been achieved to use an end-to-end unsupervised neural netw...

Motion Feature Aggregation for Video-Based Person Re-Identification.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Most video-based person re-identification (re-id) methods only focus on appearance features but neglect motion features. In fact, motion features can help to distinguish the target persons that are hard to be identified only by appearance features. H...

Football Game Video Analysis Method with Deep Learning.

Computational intelligence and neuroscience
Football is a beloved sport, and its wide audience makes football video one of the most analytically valuable types of video. Researchers have achieved certain research results in football video content analysis. How to locate interesting event clips...

Automated soccer head impact exposure tracking using video and deep learning.

Scientific reports
Head impacts are highly prevalent in sports and there is a pressing need to investigate the potential link between head impact exposure and brain injury risk. Wearable impact sensors and manual video analysis have been utilized to collect impact expo...

Validation of Machine Learning-Based Automated Surgical Instrument Annotation Using Publicly Available Intraoperative Video.

Operative neurosurgery (Hagerstown, Md.)
BACKGROUND: Intraoperative tool movement data have been demonstrated to be clinically useful in quantifying surgical performance. However, collecting this information from intraoperative video requires laborious hand annotation. The ability to automa...

A Deep Learning Approach for Quantifying Vocal Fold Dynamics During Connected Speech Using Laryngeal High-Speed Videoendoscopy.

Journal of speech, language, and hearing research : JSLHR
PURPOSE: Voice disorders are best assessed by examining vocal fold dynamics in connected speech. This can be achieved using flexible laryngeal high-speed videoendoscopy (HSV), which enables us to study vocal fold mechanics with high temporal details....

Expert surgeons and deep learning models can predict the outcome of surgical hemorrhage from 1 min of video.

Scientific reports
Major vascular injury resulting in uncontrolled bleeding is a catastrophic and often fatal complication of minimally invasive surgery. At the outset of these events, surgeons do not know how much blood will be lost or whether they will successfully c...

A CNN-based misleading video detection model.

Scientific reports
Videos, especially short videos, have become an increasingly important source of information in these years. However, many videos spread on video sharing platforms are misleading, which have negative social impacts. Therefore, it is necessary to find...

A Deep Learning and Clustering Extraction Mechanism for Recognizing the Actions of Athletes in Sports.

Computational intelligence and neuroscience
In sports, the essence of a complete technical action is a complete information structure pattern and the athlete's judgment of the action is actually the identification of the movement information structure pattern. Action recognition refers to the ...

Accurate identification of EEG recordings with interictal epileptiform discharges using a hybrid approach: Artificial intelligence supervised by human experts.

Epilepsia
OBJECTIVE: To evaluate the diagnostic performance of artificial intelligence (AI)-based algorithms for identifying the presence of interictal epileptiform discharges (IEDs) in routine (20-min) electroencephalography (EEG) recordings.