Prestandajämförelse mellan Xception, InceptionV3 och MobileNetV2 för bildklassificering på nätpaneler

Prestandajämförelse mellan Xception, InceptionV3 och MobileNetV2 för bildklassificering på nätpaneler

Under de senaste året har modeller för djupinlärning använts inom nästa alla områden, från industri till akademi, särskilt för bildklassifikation. Dessa modeller är dock enorma i storlek, med miljontals parametrar, vilket gör det svårt att distribuera till mindre enheter med begränsade resurser såso...

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Bibliographic Details
Main Author:	Birindwa, Fleury
Format:	Others
Language:	Swedish
Published:	Jönköping University, JTH, Datateknik och informatik 2020
Subjects:	image classification Machines Learning deep learning convolutional neural network CNN Xception InceptionV3 MobilNetV2 artificial intelligence AI decision bildklassificering maskininlärning djupinlärning faltningsnätverk artificiell intelligens omdömen Computer Sciences Datavetenskap (datalogi) Computer Vision and Robotics (Autonomous Systems) Datorseende och robotik (autonoma system)
Online Access:	http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-51351

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