Inaccurate Supervised Saliency Detection Based on Iterative Feedback Framework

Inaccurate Supervised Saliency Detection Based on Iterative Feedback Framework

Machine learning based bottom-up saliency detection (MLBU) methods are very popular recently. These MLBU methods firstly use prior knowledge to select some regions from the given image as training samples and label them. Based on training set, a saliency classifier is learned to classify salient obj...

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Bibliographic Details
Main Authors: Yu Pang, Yunhe Wu, Chengdong Wu, Xiaosheng Yu, Yuan Gao
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Saliency detection
prior knowledge
inaccurate supervised learning
iterative feedback classification
smoothness optimization
Online Access:https://ieeexplore.ieee.org/document/9112188/

Internet

https://ieeexplore.ieee.org/document/9112188/

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