Parallel Cascade Correlation Neural Network Methods for 3D Facial Recognition: A Preliminary Study

• 作者: Khalid Mohammad Jaber Sokyna M. Al-Qatawneh
• 来源期刊: 电脑和通信(英文)
• 学科: 工学
• 关键词: PARALLEL COMPUTING CCNNs 3D FACIAL Recognition MPI GPGPU MULTICORE
• 年，卷（期）: 2015,（5）
• 页码范围: 54-62
• 页数: 9页
• 分类号: TP39

摘要

This paper explores the possibility of using multi-core programming model that implements the Cascade correlation neural networks technique (CCNNs), to enhance the classification phase of 3D facial recognition system, after extracting robust and distinguishable features. This research provides a comprehensive summary of the 3D facial recognition systems, as well as the state-of-the- art for the Parallel Cascade Correlation Neural Networks methods (PCCNNs). Moreover, it highlights the lack of literature that combined between distributed and shared memory model which leads to novel possibility of taking advantage of the strengths of both approaches in order to construct an efficient parallel computing system for 3D facial recognition.