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Chang Yu

4 papers hereh-index 325 citations5 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author2

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV3
  • eess.IV1
same name
  • Chang Yu — 15 papers, h 6
  • Chang Yu — 10 papers, h 3
  • Chang Yu — 7 papers, h 5
  • Chang Yu — 5 papers, h 4
  • Chang Yu — 5 papers, h 4
  • Chang Yu — 3 papers, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedHaar Nuclear Norms with Applications to Remote Sensing Imagery Restoration

1 citations · 1 across the 3 of their papers we have counts for

collaborators

4 papers

cs.CV2025

A Foundation Model for DAS Signal Recognition and Visual Prompt Tuning of the Pre-trained Model for Downstream Tasks

Kun Gui, Hongliang Ren, Shang Shi +5

Distributed Acoustic Sensing (DAS) technology finds growing applications across various domains. However, data distribution disparities due to heterogeneous sensing environments po…

cs.CV2025

Cross-Frequency Implicit Neural Representation with Self-Evolving Parameters

Chang Yu, Yisi Luo, Kai Ye +2

Implicit neural representation (INR) has emerged as a powerful paradigm for visual data representation. However, classical INR methods represent data in the original space mixed wi…

cs.CV2024

Hipandas: Hyperspectral Image Joint Denoising and Super-Resolution by Image Fusion with the Panchromatic Image

Shuang Xu, Zixiang Zhao, Haowen Bai +4

Hyperspectral images (HSIs) are frequently noisy and of low resolution due to the constraints of imaging devices. Recently launched satellites can concurrently acquire HSIs and pan…

eess.IV2024★ 1 cited

Haar Nuclear Norms with Applications to Remote Sensing Imagery Restoration

Shuang Xu, Chang Yu, Jiangjun Peng +2

Remote sensing image restoration aims to reconstruct missing or corrupted areas within images. To date, low-rank based models have garnered significant interest in this field. This…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.