milania.de bewertung und analyse
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| Title | Milania’s |
| Description | Milania’s Blog jansellner.net | milania.de Blog Showcase About Informatics C++ Building and configuring OpenCV in Visual Studio 2015 with source code mapp |
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| Host IP | 85.13.138.103 |
| Location | Germany |
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milania.de bewertung
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Euro€4,408
Zuletzt aktualisiert: 2022-06-29 01:42:05
milania.de hat Semrush globalen Rang von 6,595,638. milania.de hat einen geschätzten Wert von € 4,408, basierend auf seinen geschätzten Werbeeinnahmen. milania.de empfängt jeden Tag ungefähr 551 einzelne Besucher. Sein Webserver befindet sich in Germany mit der IP-Adresse 85.13.138.103. Laut SiteAdvisor ist milania.de sicher zu besuchen. |
Verkehr & Wertschätzungen
| Kauf-/Verkaufswert | Euro€4,408 |
| Tägliche Werbeeinnahmen | Euro€120,118 |
| Monatlicher Anzeigenumsatz | Euro€40,223 |
| Jährliche Werbeeinnahmen | Euro€2,755 |
| Tägliche eindeutige Besucher | 551 |
| Hinweis: Alle Traffic- und Einnahmenwerte sind Schätzungen. | |
DNS Records
| Host | Type | TTL | Data |
| milania.de. | A | 7199 | IP: 85.13.138.103 |
| milania.de. | NS | 7200 | NS Record: ns5.kasserver.com. |
| milania.de. | NS | 7200 | NS Record: ns6.kasserver.com. |
| milania.de. | MX | 7200 | MX Record: 10 w00c57c5.kasserver.com. |
HtmlToTextCheckTime:2022-06-29 01:42:05
| Milania’s Blog jansellner.net | milania.de Blog Showcase About Informatics C++ Building and configuring OpenCV in Visual Studio 2015 with source code mapping C++ class for easy parallelization of for loops Project references in Visual Studio and C++ Compile qt’s db2 sqldriver (QDB2) Computer Vision Introduction to the Hessian feature detector for finding blobs in an image Introduction to convolution with link to filters in computer vision Scale invariance through Gaussian scale space Hardware Using the Surface pen as presenter LaTeX Define a new environment for different page numbering styles in LaTeX Triangular system of linear equations in LaTeX Neural Networks Introduction to neural network optimizers [part 3] – Adam optimizer Introduction to neural network optimizers [part 2] – adaptive learning rates (RMSProp, AdaGrad) Introduction to neural network optimizers [part 1] – momentum optimization OpenCL Buffer vs. image performance for applying filters to an image pyramid in OpenCL |
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