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ISSN Approved Journal No: 2320-2882 | Impact factor: 7.97 | ESTD Year: 2013
Call For Paper - Volume 14 | Issue 2 | Month- February 2026
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Published Paper Details:
Paper Title
Secure Vision AI: Deep Learning-Based Real-Time Violence Detection
Authors
K N Rakshitha, Lavanya S, Bindu S, Saniya Khanum
Keywords
Secure Vision AI, Violence Detection, CNN, LSTM, Deep Learning, Real-Time Surveillance, Computer Vision
Abstract
Secure Vision AI addresses the growing challenge of detecting violent and suspicious activities in video surveillance systems. Traditional monitoring methods rely heavily on human observation, which often leads to delayed responses and missed incidents. This work presents a deep learning-based real-time violence detection framework that combines Convolutional Neural Networks (CNN) for spatial feature extraction with Long Short-Term Memory (LSTM) networks for temporal analysis. Live video streams are processed, pre-processed, and analyzed to identify violent actions with high accuracy. The system generates instant alerts and securely stores detection results using Supa base for future analysis. Experimental evaluation demonstrates that the hybrid CNN-LSTM model outperforms individual models in terms of accuracy, precision, recall, and F1-score, making it suitable for real-time surveillance applications.
IJCRT's Publication Details
Unique Identification Number - IJCRT2602086
Paper ID - 301072
Page Number(s) - a754-a759
Pubished in - Volume 14 | Issue 2 | February 2026
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Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Cite this article
K N Rakshitha, Lavanya S, Bindu S, Saniya Khanum, "Secure Vision AI: Deep Learning-Based Real-Time Violence Detection", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.14, Issue 2, pp.a754-a759, February 2026, Available at :http://www.ijcrt.org/papers/IJCRT2602086.pdf
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Volume 14 | Issue 2
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Submit Manuscript Online Impact Factor: 7.97 Review Results : Within 02-03 Days Paper Publication : Within 02-03 Days
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
ISSN and 7.97 Impact Factor Details
ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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