Violence Detection Using Deep Learning

Abstract

Due to the increased risk of exposure to violent and harmful content brought about by the spread of online video content, robust systems for automatic detection and filtering have to be developed. This research suggests a novel method for deep learning-based violent content detection in videos. Our model examines both temporal and spatial characteristics in video frames by utilizing the power of recurrent neural networks (RNNs) and convolutional neural networks (CNNs).The suggested system uses a two-stream architecture, where one stream is used for temporal information using bidirectional LSTM (Long Short-Term Memory) networks to capture sequential dependencies, and the other stream is devoted to spatial analysis using 3D CNNs for frame-level understanding [1]. To ensure strong generalization, the model is additionally trained on a varied dataset that includes both violent and nonviolent content. Transfer learning is used with pre- trained deep learning models on large-scale datasets to improve the model's performance [5]. Comprehensive tests show how well the suggested method works to reliably identify violent content in videos of different genres and settings. The system demonstratesits potential for incorporation into online video platforms to give viewers a safer and more secure experience by achieving state-of-the-art outcomes in terms of precision, recall, and F1 score [4]. The suggested deep learning-based approach supports further initiatives to lessen the negative impacts of violent content in digital media and promote a safe and healthy online community [1]. Using Deep Learning to Address the Problem of Violent Video Detection: A Bright Future for Security and Safety. The proliferation of violent content is a key concern posed by the ever-increasing abundance of online video content. This puts personal safety, public safety, and platforms' capacity to properly filter information at risk. Presenting deep learning, a potent technique that presents a viable way to automatically identify violent content in videos [2]. To sum up, deep learning presents a potent and exciting way to address the pressing problem of violent video content. We can create a more secure online environment for everyone by utilizing this technology properly and resolving the issues it raises [5]. Further investigation into cross-modality learning and real-time detection shows promise for even higher efficiency and accuracy