Most of the biometric developments have been extensively utilized for diverse security applications. A deep learning-based model serves as an end to end learning framework for multimodal biometric recognition, allowing for the proper learning of feature representation. Some of the major drawbacks faced in the existing approaches are dimensionality issues, convergence problems and poor network training ability. To overcome these issues, an automated multimodal biometric recognition system is proposed