Estadístiques de Designing efficient architectures for modeling temporal features with convolutional neural networks
Visites totals
| views | |
|---|---|
| Designing efficient architectures for modeling temporal features with convolutional neural networks | 371 |
Visites totals per mes
| views | |
|---|---|
| May 2025 | 0 |
| June 2025 | 0 |
| July 2025 | 0 |
| August 2025 | 2 |
| September 2025 | 1 |
| October 2025 | 1 |
| November 2025 | 0 |
Visites al fitxer
| views | |
|---|---|
| Pons_ICASSP2017_design.pdf(legacy) | 330 |
| Pons_ICASSP2017_design.pdf | 161 |
Vistes principals per país
| views | |
|---|---|
| United States | 192 |
| France | 68 |
| Sweden | 26 |
| Spain | 23 |
| Germany | 14 |
| Japan | 13 |
| China | 4 |
| Belgium | 3 |
| Canada | 2 |
| Ireland | 2 |
| Iran | 2 |
| Mongolia | 2 |
| Nigeria | 2 |
| Slovenia | 2 |
| Ukraine | 2 |
| Australia | 1 |
| Colombia | 1 |
| United Kingdom | 1 |
| South Korea | 1 |
| Malaysia | 1 |
| Portugal | 1 |
| Russia | 1 |
| South Africa | 1 |
Visites principals per ciutat
| views | |
|---|---|
| Ashburn | 48 |
| Fairfield | 22 |
| Barcelona | 19 |
| San Ramon | 15 |
| Cambridge | 9 |
| Mountain View | 9 |
| Menlo Park | 8 |
| Seattle | 7 |
| Tokyo | 7 |
| Redwood City | 6 |
| Saitama | 6 |
| Falls Church | 4 |
| San Diego | 4 |
| Blue Bell | 3 |
| Des Moines | 3 |
| Boardman | 2 |
| Brooklyn | 2 |
| Dublin | 2 |
| Lagos | 2 |
| Rezé | 2 |
| Shenzhen | 2 |
| Stanford | 2 |
| Stockholm | 2 |
| Tustin | 2 |
| Ann Arbor | 1 |
| Antioch | 1 |
| Beijing | 1 |
| Biloxi | 1 |
| Chandler | 1 |
| Fremont | 1 |
| Fuengirola | 1 |
| Jacksonville | 1 |
| Magdeburg | 1 |
| Matosinhos | 1 |
| Montréal | 1 |
| New York | 1 |
| Oxford | 1 |
| Parsippany | 1 |
| Phoenix | 1 |
| Portland | 1 |
| Potsdam | 1 |
| Redmond | 1 |
| Saint Louis | 1 |
| San Mateo | 1 |
| Seoul | 1 |
| Shah Alam | 1 |
| Sükhbaatar | 1 |
| Ulaanbaatar | 1 |
| Valencia | 1 |
| Valladolid | 1 |
| Woodbridge | 1 |