Active learning to minimize the possible risk of future epidemics
Future epidemics are inevitable, and it takes months and even years to collect fully annotated data. The sheer magnitude of data required for machine learning algorithms, spanning both shallow and deep structures, raises a fundamental question: how big data is big enough to effectively tackle future...
| Main Author: | Santosh, K. C., |
|---|---|
| Other Authors: | Nakarmi, Suprim,, SpringerLink (Online Service) |
| Format: | eBook |
| Language: | English |
| Published: |
Singapore :
Springer,
[2023]
|
| Physical Description: |
1 online resource (xvi, 96 pages) : illustrations. |
| Series: |
SpringerBriefs in applied sciences and technology.
SpringerBriefs in applied sciences and technology. Computational intelligence. |
| Subjects: |
CMU Electronic Access
Electronic Resource Click Here| Location | Call Number: | Status |
|---|---|---|
| CMU Electronic Access | Available |