Catalogue of Tools & Metrics for Trustworthy AI

These tools and metrics are designed to help AI actors develop and use trustworthy AI systems and applications that respect human rights and are fair, transparent, explainable, robust, secure and safe.

Crime Detection using Deep learning



Crime Detection  using Deep learning

Performed crime detection on crime data manually collected from Google images as well as the Imagenet database.

Crime detection is one of the highly useful applications in the field of deep learning, as this helps in curbing crime and increasing the safety of people. Developed an object detection model using YOLO Darknet to detect harmful weapons such as guns and knives, in the hands of a person. This ensures the prevention of false alarms by detecting just the gun or a knife. Also trained the model to detect a person lying down on the road, which helps 911 emergency to reach on time to save the life of the person.

Trained the model for 40000 iterations using pre-trained weights file convolutional layer: http://pjreddie.com/media/files/darknet19_448.conv.23

Sample Output of Detection

Output.png

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Disclaimer: The tools and metrics featured herein are solely those of the originating authors and are not vetted or endorsed by the OECD or its member countries. The Organisation cannot be held responsible for possible issues resulting from the posting of links to third parties' tools and metrics on this catalogue. More on the methodology can be found at https://oecd.ai/catalogue/faq.