Chao Zhang

Orcid: 0000-0002-7705-8505

Affiliations:
  • University of Electronic Science and Technology of China, School of Information and Communication Engineering, Chengdu, China
  • Sichuan Police College, Luzhou, China


According to our database1, Chao Zhang authored at least 12 papers between 2017 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

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Bibliography

2023
Blind image deblurring via content adaptive method.
Signal Process. Image Commun., April, 2023

Concept Lattice Factorization in Social Networks.
Proceedings of the 7th International Conference on Big Data and Internet of Things, 2023

Heterogeneous-training: A Semi-supervised Text Classification Method.
Proceedings of the 7th International Conference on Big Data and Internet of Things, 2023

2022
MA-GANet: A Multi-Attention Generative Adversarial Network for Defocus Blur Detection.
IEEE Trans. Image Process., 2022

Mutual-Guidance Transformer-Embedding Network for Video Salient Object Detection.
IEEE Signal Process. Lett., 2022

2021
AFDet: Toward More Accurate and Faster Object Detection in Remote Sensing Images.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021

2020
MultiANet: a Multi-Attention Network for Defocus Blur Detection.
Proceedings of the 22nd IEEE International Workshop on Multimedia Signal Processing, 2020

2019
Revisiting image ordinal estimation: how to deal with ordinal relationship in deep learning?
J. Electronic Imaging, 2019

C3AE: Exploring the Limits of Compact Model for Age Estimation.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018
Visual aesthetic understanding: Sample-specific aesthetic classification and deep activation map visualization.
Signal Process. Image Commun., 2018

Image Ordinal Classification and Understanding: Grid Dropout with Masking Label.
Proceedings of the 2018 IEEE International Conference on Multimedia and Expo, 2018

2017
Image ordinal estimation: Classification and regression benefit each other.
Proceedings of the 2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, 2017


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