内田 誠一

Computer Science

1. Character Recognition 100%
2. Experimental Result 75%
3. Classes 67%
4. Simulation Mode 64%
5. Detection 59%
6. Classification 54%
7. Algorithms 48%
8. Dynamic Programming 47%
9. Networks 44%
10. Optical Character Recognition 43%
11. Accuracy 42%
12. Pattern Recognition 32%
13. Evaluation 31%
14. Neural Network 30%
15. Database 28%
16. Recognition Rate 28%
17. Recognition Accuracy 26%
18. Signature Verification 24%
19. Representation 23%
20. Classification (Machine Learning) 23%
21. Vectors 22%
22. Application 21%
23. Recognition Result 20%
24. Embedding Data 19%
25. Segmentation 18%
26. Functions 17%
27. Generation 17%
28. Design 17%
29. Image Matching 17%
30. Convolutional Neural Network 15%
31. Correlation 15%
32. Generative Adversarial Networks 15%
33. Relationships 15%
34. Computation 15%
35. Invariants 14%
36. Image Processing 14%
37. Feature Space 14%
38. Nearest Neighbour 14%
39. Affine Invariant 14%
40. Embedding 14%
41. Global Feature 13%
42. User 13%
43. Contexts 12%
44. Annotation 12%
45. Sequential Pattern 12%
46. Machine Learning 12%
47. Image Retrieval 11%
48. U-Net 11%
49. Support Vector Machine 11%
50. Neighbourhood Graph 10%