Research on Collaborative Salient Object Detection Using Collaborative Feature Integration and Extraction-Reference-Cited by-同舟云学术

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Research on Collaborative Salient Object Detection Using Collaborative Feature Integration and Extraction

Published:2024-03-08 Issue: Volume:PP Page:152-159
ISSN:
Container-title:2024 12th International Conference on Intelligent Control and Information Processing (ICICIP)
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Author:

Chen Yachun¹,Lu Mengqi²,Sun Yu¹,Zhang Nina³,Zhou Yanlong¹,Zhang Dehua¹

Affiliation:

1. College of Artificial Intelligence, Henan University,Zhengzhou,China

2. Miami College, Henan University,Zhengzhou,China

3. Comprehensive Information Support Center, Shaanxi General Staff of PAP,Xi'an,China

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10477678/10477778/10477810.pdf?arnumber=10477810

Reference16 articles.

1. Two Birds With One Stone: A Unified Approach to Saliency and Co-Saliency Detection via Multi-Instance Learning

2. GSNNet: Group semantic-guided neighbor interaction network for co-salient object detection

3. Co-salient object detection based on deep saliency networks and seed propagation over an integrated graph;Dong-Ju;IEEE Transactions on Image Processing,2017

4. Evaluation of performance over various pre-trained deepconvolutional neural network models for co-saliency detection problem

5. AMP: Adaptive Masked Proxies for Few-Shot Segmentation

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