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Semi-Self-Supervised Learning for Semantic Segmentation in Images with Dense Patterns

Plant Phenomics 2023年第2期5卷 149-163页

作者： Keyhan Najafian Alireza Ghanbari Mahdi Sabet Kish Mark Eramian Gholam Hassan Shirdel Ian Stavness Lingling Jin farhad maleki Department of Computer Science University of SaskatchewanSaskatoonSaskatchewanCanada Mathematics Department Faculty of SciencesUniversity of QomQomIran Department of Mathematics Faculty of Mathematical ScienceShahid Beheshti UniversityTehranIran Department of Computer Science University of CalgaryCalgaryAlbertaCanada

Deep learning has shown potential in domains with large-scale annotated ***,manual annotation is expensive,time-consuming,and ***-level annotations are particularly costly for semantic segmentation in images with dense irregular patterns of object instances,such as in plant *** this work,we propose a method for developing high-performing deep learning models for semantic segmentation of such images utilizing little manual *** a use case,we focus on wheat head *** synthesize a computationally annotated dataset—using a few annotated images,a short unannotated video clip of a wheat field,and several video clips with no wheat—to train a customized U-Net *** the distribution shift between the synthesized and real images,we apply three domain adaptation steps to gradually bridge the domain *** using two annotated images,we achieved a Dice score of 0.89 on the internal test *** further evaluated on a diverse external dataset collected from 18 different domains across five countries,this model achieved a Dice score of *** expose the model to images from different growth stages and environmental conditions,we incorporated two annotated images from each of the 18 domains to further fine-tune the *** increased the Dice score to *** result highlights the utility of the proposed approach in the absence of large-annotated *** our use case is wheat head segmentation,the proposed approach can be extended to other segmentation tasks with similar characteristics of irregularly repeating patterns of object instances.

关键词： instance utilizing consuming

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