An Optimization Method of Deep Transfer Learning for Vegetation Segmentation under Rainy and Dry Season Differences in a Dry Thermal Valley

Deep learning networks might require re-training for different datasets, consuming significant manual labeling and training time. Transfer learning uses little new data and training time to enable pre-trained network segmentation in relevant scenarios (e.g., different vegetation images in rainy and...

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Detalles Bibliográficos
Autores principales: Chen, Yayong, Zhou, Beibei, Ye, Dapeng, Cui, Lei, Feng, Lei, Han, Xiaojie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10574146/
https://www.ncbi.nlm.nih.gov/pubmed/37836123
http://dx.doi.org/10.3390/plants12193383

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10574146/
https://www.ncbi.nlm.nih.gov/pubmed/37836123
http://dx.doi.org/10.3390/plants12193383

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