Synthetic Aperture Radar (SAR) Data Applications
- Indbinding:
- Paperback
- Sideantal:
- 288
- Udgivet:
- 20. januar 2024
- Udgave:
- 24001
- Størrelse:
- 155x16x235 mm.
- Vægt:
- 441 g.
- 8-11 hverdage.
- 20. november 2024
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- 1 valgfrit digitalt ugeblad
- 20 timers lytning og læsning
- Adgang til 70.000+ titler
- Ingen binding
Abonnementet koster 75 kr./md.
Ingen binding og kan opsiges når som helst.
Beskrivelse af Synthetic Aperture Radar (SAR) Data Applications
This carefully curated volume presents an in-depth, state-of-the-art discussion on many applications of Synthetic Aperture Radar (SAR). Integrating interdisciplinary sciences, the book features novel ideas, quantitative methods, and research results, promising to advance computational practices and technologies within the academic and industrial communities. SAR applications employ diverse and often complex computational methods rooted in machine learning, estimation, statistical learning, inversion models, and empirical models. Current and emerging applications of SAR data for earth observation, object detection and recognition, change detection, navigation, and interference mitigation are highlighted. Cutting edge methods, with particular emphasis on machine learning, are included. Contemporary deep learning models in object detection and recognition in SAR imagery with corresponding feature extraction and training schemes are considered. State-of-the-art neural network architectures in SAR-aided navigation are compared and discussed further. Advanced empirical and machine learning models in retrieving land and ocean information ¿ wind, wave, soil conditions, among others, are also included.
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Bogen Synthetic Aperture Radar (SAR) Data Applications findes i følgende kategorier:
- Business og læring > Computer og IT
- Matematik og naturvidenskab > Matematik > Sandsynlighedsregning og statistik
- Matematik og naturvidenskab > Matematik > Optimalisering
- Databehandling og informationsteknologi > Databaser
- Databehandling og informationsteknologi > Informatik > Kunstig intelligens > Machine learning
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