Faster nonconvex low-rank matrix learning for image low-level and high-level vision: a unified framework
This study introduces a unified approach to tackle challenges in both low-level and high-level vision tasks for image processing. The framework integrates faster nonconvex low-rank matrix computations and continuity techniques to yield efficient and high-quality results. In addressing real-world ima...
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Main Authors: | Zhang, Hengmin, Yang, Jian, Qian, Jianjun, Gong, Chen, Ning, Xin, Zha, Zhiyuan, Wen, Bihan |
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Other Authors: | School of Electrical and Electronic Engineering |
Format: | Article |
Language: | English |
Published: |
2024
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/179153 |
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Institution: | Nanyang Technological University |
Language: | English |
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