Faster nonconvex low-rank matrix learning for image low-level and high-level vision: a unified framework

• المؤلفون الرئيسيون: Zhang, Hengmin, Yang, Jian, Qian, Jianjun, Gong, Chen, Ning, Xin, Zha, Zhiyuan, Wen, Bihan
• مؤلفون آخرون: School of Electrical and Electronic Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2024
• الموضوعات: Engineering; Faster low-rank matrix learning; Nonconvex PBCD algorithm
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/179153
• المؤسسة: Nanyang Technological University

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...