Intelligent Criminal Identification System Based on ML & Recognition Technologies
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| Formato: | Recurso digital |
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Zenodo
2025
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| _version_ | 1866902164739194880 |
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| author | Naripeddi.Kavya, Mrs. CH. Naga Lakshmi |
| author_facet | Naripeddi.Kavya, Mrs. CH. Naga Lakshmi |
| contents | <p>The Intelligent Criminal Identification System is based on the Machine Learning (ML) and facial recognition<br>technologies with the aim to increase the effectiveness and precision of criminal identification. Due to the demand<br>of efficient surveillance systems and the rise of crimes and criminal activities, the given project is focused on<br>automating the identifying and tracking process of individuals using their facial features. Conventional procedures<br>tend to be time consuming, laborious and liable to human mistakes. In a bid to overcome these problems, the<br>proposed system runs the facial images, either through real time CCTV or web cam imaging, or uploaded as input,<br>through state of the art face detection algorithms. Special algorithms are used to extract distinctive face features and<br>compare them to an existing criminal database to find possible matches. An alert is produced on finding a match to<br>be investigated. The system is based on using Python, OpenCV to process the images and TensorFlow or Keras to<br>train deep learning models. They use Haar Cascade classifiers or MTCNN to detect faces and such models as<br>FaceNet or DeepFace to embed feature vectors of 128 dimensions. These vectors are used subsequently with<br>classification algorithms including Support Vector Machines (SVM), Random Forest, and K-nearest neighbors<br>(KNN) to detect criminals with high accuracy levels.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_15740003 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Intelligent Criminal Identification System Based on ML & Recognition Technologies Naripeddi.Kavya, Mrs. CH. Naga Lakshmi <p>The Intelligent Criminal Identification System is based on the Machine Learning (ML) and facial recognition<br>technologies with the aim to increase the effectiveness and precision of criminal identification. Due to the demand<br>of efficient surveillance systems and the rise of crimes and criminal activities, the given project is focused on<br>automating the identifying and tracking process of individuals using their facial features. Conventional procedures<br>tend to be time consuming, laborious and liable to human mistakes. In a bid to overcome these problems, the<br>proposed system runs the facial images, either through real time CCTV or web cam imaging, or uploaded as input,<br>through state of the art face detection algorithms. Special algorithms are used to extract distinctive face features and<br>compare them to an existing criminal database to find possible matches. An alert is produced on finding a match to<br>be investigated. The system is based on using Python, OpenCV to process the images and TensorFlow or Keras to<br>train deep learning models. They use Haar Cascade classifiers or MTCNN to detect faces and such models as<br>FaceNet or DeepFace to embed feature vectors of 128 dimensions. These vectors are used subsequently with<br>classification algorithms including Support Vector Machines (SVM), Random Forest, and K-nearest neighbors<br>(KNN) to detect criminals with high accuracy levels.</p> |
| title | Intelligent Criminal Identification System Based on ML & Recognition Technologies |
| url | https://doi.org/10.5281/zenodo.15740003 |