This creates challenges for pedestrian dead reckoning (PDR) using the inertial ... compared to conventional CNN structures while achieving $\mathbf{9 6. 4 5 \%}$ accuracy in activity classification.

This research paper delves into the application of deep CNNs for human emotion detection. Leveraging datasets rich in annotated facial expressions, our study explores the architecture and training ...

Abstract: Traditional Human Activity Recognition (HAR) approaches often rely on handcrafted features and incomplete feature extraction, limiting their effectiveness. To address these challenges, we ...

Australia’s financial intelligence agency has fined Melbourne-based crypto exchange Cointree $75,120 for failing to submit suspicious activity reports within the required timeframe. The Australian ...

Abstract: The need to detect suspicious activities ... in those on anomaly detection in video surveillance using different machine learning and deep learning techniques which have been explored till ...

Road object detection at high accuracy and fast inference speed is a challenging task for safe autonomous driving as false positives arising from false localization can lead to fatal outcomes. The ...

Therefore, the detection of abnormal events in videos is an important research topic. In this paper, an improved deep learning model TCNN-LSTM is obtained by combining CNN with LSTM. We carried out ...