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DSFMA: deeply supervised fully convolutional neural networks based on multi-level aggregation for saliency detection
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Affiliation of Author(s): : 软件学院

Title of Paper: : DSFMA: deeply supervised fully convolutional neural networks based on multi-level aggregation for saliency detection

Journal: : Multimedia Tools and Applications

First Author: : Inam Ullah

Indexed by: : Unit Twenty Basic Research

Document Code: : 2ED773D448F74D49B815A60564813530

Translation or Not: : no

Date of Publication: : 2019-10-26

Personal information

Associate Professor

Gender : Female

Alma Mater : 山东大学

Education Level : With Certificate of Graduation for Doctorate Study

Degree : Doctor

Status : Employed

School/Department : 软件学院

Date of Employment : 1998-07-16

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