mathematical modeling, percolation theory, probability theory, swarm of robots.
In this paper, we propose an incremental learning scheme for the abnormal behavior detection algorithm based on principal component. The results obtained on a UCSD dataset and our experimental videos at a different number of training samples show that error rates are similar to conventional learning...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Samara National Research University
2020-06-01
|
| Series: | Компьютерная оптика |
| Subjects: | |
| Online Access: | http://computeroptics.smr.ru/KO/PDF/KO44-3/440320.pdf |
| Summary: | In this paper, we propose an incremental learning scheme for the abnormal behavior detection algorithm based on principal component. The results obtained on a UCSD dataset and our experimental videos at a different number of training samples show that error rates are similar to conventional learning. Moreover, the proposed scheme allows the incremental learning time to be significantly reduced in comparison with a method based on matrix eigendecomposition. |
|---|---|
| ISSN: | 0134-2452 2412-6179 |