Weakly Supervised Conditional Random Fields Model for Semantic Segmentation with Image Patches
نویسندگان
چکیده
منابع مشابه
Amortized Inference and Learning in Latent Conditional Random Fields for Weakly-Supervised Semantic Image Segmentation
Conditional random fields (CRFs) are commonly employed as a post-processing tool for image segmentation tasks. The unary potentials of the CRF are often learnt independently by a classifier, thereby decoupling the inference in CRF from the training of classifier. Such a scheme works effectively, when pixel-level labelling is available for all the images. However, in absence of pixel-level label...
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ژورنال
عنوان ژورنال: Applied Sciences
سال: 2020
ISSN: 2076-3417
DOI: 10.3390/app10051679