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搞不懂の晴天

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iEEE Access收到意见，两个接收修改，一个拒稿不建议重投，意见是Reviewer: 3

Recommendation: Reject (do not encourage resubmit)

Comments:
I cannot recommend the acceptance of this work for the following reasons:
1. Limited novelty. The use of low rank prior and iterative method for image inpainting has been widely studied in the literature since 2010. It is difficult to tell what is the fundamentally new insight brought by this paper especially in view of recent publications (e.g., refs. [28] and [30]). The paper contains several mathematical claims&proofs, but I have found they do not contain sufficiently new results. Meantime, I think there is a gap between the developed mathematical theory and the application into real-world images (e.g., the approximation of non-convexity).
2. Unconvincing experimental results. The reported experimental results do not demonstrate better performance than previous state-of-the-art such as TSLRA [28]. The authors have only considered low-rank based inpainting methods and totally overlooked recently developed deep learning-based image inpainting. Therefore it is difficult to evaluate how this work is compared with the current state-of-the-art.
3. Poor literary presentation. The paper is not well-written and contains many grammatical errors. It is suggested that this paper be proofread by someone whose native language is English before the resubmission.

Additional Questions:
Does the paper contribute to the body of knowledge?: Very little in my opinion.

Is the paper technically sound?: Yes.

Is the subject matter presented in a comprehensive manner?: Not always.

Are the references provided applicable and sufficient?: No. Recent works on deep learning based image inpainting are missing.
请问，这该如何是好？怎么回复这样尖锐的问题呢？再投的机会大不大？

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