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Obada Issa and Tamer Shanableh
This paper proposes a novel approach to activity recognition where videos are compressed using video coding to generate feature vectors based on compression variables. We propose to eliminate the temporal domain of feature vectors by computing the mean a...
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Danila Germanese, Sara Colantonio, Marco Del Coco, Pierluigi Carcagnì and Marco Leo
Computer vision is a powerful tool for healthcare applications since it can provide objective diagnosis and assessment of pathologies, not depending on clinicians? skills and experiences. It can also help speed-up population screening, reducing health ca...
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Walaa H. Elashmawi, John Emad, Ahmed Serag, Karim Khaled, Ahmed Yehia, Karim Mohamed, Hager Sobeah and Ahmed Ali
New guitarists face multiple problems when first starting out, and these mainly stem from a flood of information that they are presented with. Students also typically struggle with proper pitch frequency recognition and accurate left-hand motion. A varie...
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Shukai Li, Xiaofang Wang, Dongri Shan and Peng Zhang
Temporal modeling is a key problem in action recognition, and it remains difficult to accurately model temporal information of videos. In this paper, we present a local spatiotemporal extraction module (LSTE) and a channel time excitation module (CTE), w...
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Wensheng Chen, Yinxi Niu, Zhenhua Gan, Baoping Xiong and Shan Huang
Enhancing information representation in electromyography (EMG) signals is pivotal for interpreting human movement intentions. Traditional methods often concentrate on specific aspects of EMG signals, such as the time or frequency domains, while overlooki...
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