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This document presents a novel gun detection model that utilizes advanced deep learning techniques, specifically CNN-based architectures, to automate handgun identification in surveillance footage. The proposed multi-model fusion approach integrates suspicious motion detection, gun appearance recognition, and human pose estimation to enhance the robustness of threat detection in complex environments. The paper outlines the methodology, dataset construction, and evaluation strategies, demonstrating the model

Author

23ucs562

Language

EN