Transfer learning between crop types for semantic segmentation of crops versus weeds in precision agriculture
Author:
Affiliation:
1. School of Computer ScienceUniversity of LincolnLincoln UK
2. Institute of Information TechnologiesGebze Technical UniversityGebze Kocaeli Turkey
Publisher
Wiley
Subject
Computer Science Applications,Control and Systems Engineering
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1002/rob.21869
Reference28 articles.
1. SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
2. Analysis of Morphology-Based Features for Classification of Crop and Weeds in Precision Agriculture
3. Connected attribute morphology for unified vegetation segmentation and classification in precision agriculture
4. Semantic object classes in video: A high-definition ground truth database
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