Visual saliency detection via invariant feature constrained stacked denoising autoencoder

Visual saliency detection is usually regarded as an image pre-processing method to predict and locate the position and shape of saliency regions. However, many existing saliency detection methods can only obtain the local or even incorrect position and shape of saliency regions, resulting in incompl...

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Veröffentlicht in:	Multimedia tools and applications Jg. 82; H. 18; S. 27451 - 27472
Hauptverfasser:	Ma, Yunpeng, Yu, Zhihong, Zhou, Yaqin, Xu, Chang, Yu, Dabing
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.07.2023 Springer Nature B.V
Schlagworte:	Accuracy Belief networks Bias Computer Communication Networks Computer Science Data Structures and Information Theory Deep learning Image reconstruction Image restoration Image retrieval Image segmentation Invariants Laboratories Methods Multimedia Multimedia Information Systems Neural networks Noise reduction Object recognition Parameters Salience Special Purpose and Application-Based Systems Visual saliency detection Scale invariant feature Saliency prediction Saliency object segmentation Stacked denoising autoencoder Reconstruction network
ISSN:	1380-7501, 1573-7721
Online-Zugang:	Volltext
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