Iwana Brian Kenji

Computer Science

1. Networks 100%
2. Classification 65%
3. Simulation Mode 61%
4. Neural Network 53%
5. Pattern Recognition 41%
6. Classes 37%
7. Convolutional Neural Network 36%
8. Accuracy 34%
9. Signature Verification 32%
10. Representation 28%
11. U-Net 28%
12. Generation 25%
13. Experimental Result 25%
14. Design 23%
15. Time Series Data 23%
16. Image Processing 18%
17. Embedding 17%
18. Algorithms 15%
19. Machine Learning 15%
20. Application 15%
21. Evaluation 15%
22. Vectors 15%
23. Embedding Space 14%
24. Classification (Machine Learning) 14%
25. References 14%
26. Discriminative Power 12%
27. Functions 11%
28. Large Data Set 11%
29. Artificial Neural Network 10%
30. Art Performance 10%
31. Verification System 9%
32. Identification 9%
33. Global Feature 9%
34. Location Information 9%
35. Deep Feature 9%
36. Sample Pattern 9%
37. Feature Extraction 9%
38. Generative Adversarial Networks 9%
39. Neighbor Method 9%
40. Siamese Neural Network 9%
41. Long Short-Term Memory Network 9%
42. Gating Network 9%
43. Connected Component 9%
44. Procedures 9%
45. Survey 9%
46. Quantitative Analysis 9%
47. Nearest Neighbour 9%
48. Convolutional Network 9%
49. Dynamic Programming 9%
50. Models 9%