Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
Neural Networks and Rules-based Systems used to Find Rational and
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The application of state-of-the-art in deep learning detection algorithms, such as You Only Look Once (YOLO) and Single Shot MultiBox Detector (SSD), presents a significant opportunity for enhancing crime prevention and control strategies. This research focuses on leveraging the SSD algorithm to detect common crime weapons on individuals in both pre-crime video scenes and real-world crime scenarios. By thoroughly understanding the operational principles of the SSD algorithm, we adapted it for the identification of dangerous weapons commonly associated with violent crimes. Our detection model, which targets both weapons and individuals, establishes a robust foundation for an artificial intelligence (AI) system that accurately predicts individuals at high risk. The model first identifies the presence of a person and subsequently checks for any of the specified weapons. If a weapon is detected, the system further analyzes the individual’s movement and speed within the frame of reference. Should the individual exceed a predetermined movement threshold, the system flags them as high risk.
Yusuff Adeniyi Giwa. 2026. \u201cAdvancing Real-Time Crime Weapon Detection and High-Risk Person Classification in Pre-Crime Scenes: A Comprehensive Machine Vision Approach Utilizing SSD Detector\u201d. Global Journal of Computer Science and Technology - D: Neural & AI GJCST-D Volume 25 (GJCST Volume 25 Issue D1): .
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
The methods for personal identification and authentication are no exception.
Total Score: 133
Country: United Kingdom
Subject: Global Journal of Computer Science and Technology - D: Neural & AI
Authors: Taiwo. M. Akinmuyisitan, John Cosmas, Boluwaji Benard Akinmuyisitan (PhD/Dr. count: 0)
View Count (all-time): 165
Total Views (Real + Logic): 733
Total Downloads (simulated): 22
Publish Date: 2026 01, Fri
Monthly Totals (Real + Logic):
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The application of state-of-the-art in deep learning detection algorithms, such as You Only Look Once (YOLO) and Single Shot MultiBox Detector (SSD), presents a significant opportunity for enhancing crime prevention and control strategies. This research focuses on leveraging the SSD algorithm to detect common crime weapons on individuals in both pre-crime video scenes and real-world crime scenarios. By thoroughly understanding the operational principles of the SSD algorithm, we adapted it for the identification of dangerous weapons commonly associated with violent crimes. Our detection model, which targets both weapons and individuals, establishes a robust foundation for an artificial intelligence (AI) system that accurately predicts individuals at high risk. The model first identifies the presence of a person and subsequently checks for any of the specified weapons. If a weapon is detected, the system further analyzes the individual’s movement and speed within the frame of reference. Should the individual exceed a predetermined movement threshold, the system flags them as high risk.
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