Search Results - (( variable extraction path algorithm ) OR ( frames interactive learning algorithm ))
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Particle swarm optimization with deep learning for human action recognition
Published 2021“…We infer that our approach helps improve the tracking stability and increases the robustness of the tracking process by an accuracy of 97.09 on the Stony Brook University interaction dataset, 98.02 on the High-level Human Interaction Recognition Challenge interaction dataset, 96.17 on the Weizmann dataset. …”
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Perceptions and practices of blended learning in foreign language teaching at USIM
Published 2024journal::journal article -
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Enhanced emotion recognition in videos: a convolutional neural network strategy for human facial expression detection and classification
Published 2023“…Automated emotion recognition has garnered increasing interest due to its potential applications in various fields, such as human-computer interaction, machine learning, robotic control, and driver emotional state monitoring. …”
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Vision-Based Hand Detection and Tracking Using Fusion of Kernelized Correlation Filter and Single-Shot Detection
Published 2023“…This study explores the use of deep learning techniques for fast and robust hand detection and tracking. …”
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CNN architectures for road surface wetness classification from acoustic signals
“…Recorded acoustic signals were segmented into equal frames and thirteen MFCCs were extracted for each frame to train the CNNs. …”
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A review of slicing techniques in software engineering
Published 2015“…A common practice now is to extract the sub models out of the giant models based upon the slicing criteria. …”
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Proceeding Paper -
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Vision-Based Hand Detection and Tracking Using Fusion of Kernelized Correlation Filter and Single-Shot Detection
Published 2023“…This study explores the use of deep learning techniques for fast and robust hand detection and tracking. …”
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Magnetic resonance imaging sense reconstruction system using FPGA / Muhammad Faisal Siddiqui
Published 2016“…Furthermore, variable databus widths are used in the data path of the proposed architecture, which leads to reducing the hardware cost and silicon area. …”
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