AUTOMAZIONE DELL'ESTRAZIONE DI CARATTERISTICHE STRADALI DA IMMAGINI AD ALTA RISOLUZIONE
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Questo studio mira a sviluppare un metodo accurato di estrazione delle strade senza sacrificare l'efficienza computazionale. Proponiamo una rete neurale di segmentazione semantica che combina l'apprendimento per trasferimento e l'architettura U-net con una complessità minima.
Le tecniche di post-elaborazione sono impiegate per migliorare la qualità dell'output. Il nostro metodo raggiunge un punteggio F1 di 0,83 e un'accuratezza del 95,57%, superando altri modelli sul set di dati del Massachusetts.
Questo approccio dimostra prestazioni superiori e una ridotta complessità della rete rispetto ai metodi esistenti. .
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£27.18
£28.33 -
£10.58
£12.58 -
£16.71
£17.13
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