Statistik för Improving Defect Localization by Classifying the Affected Asset using Machine Learning
Totalt antal besök
| views | |
|---|---|
| Improving Defect Localization by Classifying the Affected Asset using Machine Learning | 61 |
Totalt antal besök per månad
| views | |
|---|---|
| June 2023 | 0 |
| July 2023 | 0 |
| August 2023 | 0 |
| September 2023 | 0 |
| October 2023 | 0 |
| November 2023 | 0 |
| December 2023 | 0 |
Nedladdningar
| views | |
|---|---|
| 255339.pdf | 120 |
Visningar per land (topp)
| views | |
|---|---|
| Sweden | 25 |
| United States | 18 |
| China | 6 |
| United Kingdom | 2 |
| Austria | 1 |
| Canada | 1 |
| India | 1 |
| Iran | 1 |
| Japan | 1 |
| South Korea | 1 |
| Latvia | 1 |
| Singapore | 1 |
| Turkey | 1 |
| Taiwan | 1 |
Visningar per stad (topp)
| views | |
|---|---|
| San Mateo | 10 |
| Gothenburg | 8 |
| Södertälje | 4 |
| Des Moines | 3 |
| Beijing | 2 |
| Moelndal | 2 |
| Alingsas | 1 |
| Calgary | 1 |
| Hachiōji | 1 |
| Hallstahammar | 1 |
| Linz | 1 |
| London | 1 |
| Mashhad | 1 |
| Nanjing | 1 |
| Norrtaelje | 1 |
| Partille | 1 |
| Riga | 1 |
| Seoul | 1 |
| Sheffield | 1 |
| Singapore | 1 |
| Sivas | 1 |
| Taichung | 1 |
| Vaestra Froelunda | 1 |
| Zhengzhou | 1 |
| Örebro | 1 |