TY - JOUR AU - Lahasan, Badr AU - Samma, Hussein PY - 2021/11/16 Y2 - 2024/03/28 TI - Convolutional Neural Network for Skull Recognition JF - International Journal of Innovative Computing JA - Int J Innov Comp VL - 12 IS - 1 SE - Computer Science DO - 10.11113/ijic.v12n1.347 UR - https://ijic.utm.my/index.php/ijic/article/view/347 SP - 55-58 AB - <p>Automatic skull identification systems play a vital role for forensic law authorities to recognize victim identity.  Motivated by potential applications of these kinds of systems, this research aims to apply a pre-trained deep convolutional neural network (CNN) for face skull recognition. Basically, the unknown skull image is fed to a pre-trained CNN network to extract a 1D feature vector, and then it will be matched with photos at database agencies to identify the closest match. To validate the proposed skull recognition system, it has been applied for a total of 13 skulls, and the reported results indicated a good was achieved. In addition, various CNN architectures were investigated, including shallow, medium, and deep CNN models. The best performance was reported from the shallow CNN model with a 92% recognition rate.  </p> ER -