1. Face Recognition Using Artificial Neural Network Group-based Adaptive Tolerance Trees
By Ming Zhang , John Fulcher

2. Revies:Group Theory

3. Review:NN Group Theory

4. Translation-invariant face recognition system

5. NN group-based tree node

6. NN group-based tree node

7. The Features of OR NN group

8. Advantage
No single neural network is capable of approximating such a function comprising three peaks and nonsmooth , noncontinuous points

9. The Features of AND NN group

10. Advantage
No single neural network is capable of approximating such a function comprising sole-peak and nonsmooth , and /or noncontinuous points

11. Both OR and AND NN groups were used as the nodes for GAT tree, resulting in more accurate and efficient face recognition .

12. NN group-base adaptive tolerance tree.

13. GAT tree model

14. OPT
Translation operator that can translate facial image MI(I,j) into a center face, left face, right face and so on --- shifts and rotates the facial image in two dimensions.(but only during training )

15. OPA
Adaptive node operator set that adds adaptive connection and grows nodes in the GAT tree if the parent node output is within tolerance.

16. OPN
Node operator set, which is a complex pattern classifier.

17. OPP
Path operator set which sets the parent node output to the input of the child node.

18. OPL
Label leaf operator set which indicates the labeled person has been recognized.

19. Face perspective classification using GAT tree

20. Face perspective classification results

21. Face perspective classification results

22. Face perspective classification results

23. Front glasses and beard face classification using GAT tree.

24. Front beard face and Front glasses face classification

25. Front beard face and Front glasses face classification

26. GAT tree for front face recognition

27. Conclusion