Facial reconstruction, or facial approximation, is an essential problem in a
criminal investigation involving reconstructing a victim's face from his skull
to determine the victim's identification at a crime scene. Facial approximation
plays a crucial part when there is a lack of clues with investigators.
Investigators utilize facial approximation to guess the victims' identities. This
research attempted to use computer-aided face reconstruction rather than
traditional approaches. Traditional methods of face reconstruction include the
use of clay or gypsum. Traditional procedures necessitate forensic
professionals to rebuild the victim's face. This research uses the convolution
neural network skull part with sift (CNNSPS) model is employed to
reconstruct facial features from a skull image utilizing public datasets
CelebAMask-HQ and MUG500+. The proposed algorithm was tested on
unidentified skull databases, and celebrity faces were used. The genuine
datasets are not available, which is the key issue in this research