[交流] 小白第一次投稿请大家帮忙看看审稿意见该怎么回复？

着急毕业投了一个mdpi旗下的水刊，投稿将近一个月收到了两个审稿人意见，然后编辑就发了邮件pending major revision，给了10天时间要求大修（第三个审稿人还没回复），第一次投稿没啥经验，想请大家帮忙参谋一下应该按照什么方向来改呢？ 第一个审稿人打分虽然相对比较高，但是他觉得创新性不够建议以letter形式发表(我自己确实也觉得创新性不够，但是创新点这个东西比较主观，而且投稿的毕竟是水刊)；第二个审稿人虽然打分没有第一个高，但问题都直击要害，应该是很懂行的专家，不过感觉认真回答问题，改一改补充一点实验还是比较好过的，没有对文章的创新性提出质疑。 问题就是我现在不知道是否应该改成letter，毕竟这样改动还是很大的，由于第二个审稿人的问题中需要有补充实验的地方，怕时间来不及，而且改成letter的话会减少很多实验，不知道第二个审稿人会不会不同意，但是不改letter的话又怕第一个审稿人直接拒，或者说有没有什么比较好的方式回答第一个审稿人关于创新性的质疑呢(同时看审稿意见我感觉第一个审稿人没有特别仔细读我的文章，有些地方理解的跟我想表达的甚至跟第二个审稿人理解的明显不一样)…想请大家帮忙看看这种情况应该怎么改呢？附图分别是第一个和第二个审稿人的打分 下面是两个审稿人的总体意见： 审稿人一： this paper proposed a deep learning based demosaicking method using several existing techniques, such as the unet++ framework, residual in residual dense block, and depthwise separable convolutions. in particular, the framework inserts densely connected layer blocks that adopt depthwise separable convolutions to reduce the number of parameters. the main novelty of the paper is that: deploying the gaussian smoothing layer into the cnn framework can expand the receptive field without down-sampling image size, achieving the fastest execution time and modest quality performance relative to the considered demosaicking methods.??because the novelty in this paper is limited, we recommend that this paper should be revised and shortened for possible publication as a `letter'. 审稿人二： the authors present a method for fast and efficient demosaicking. the manuscript contains some interesting ideas and experiments comparing the performance of their method to other methods. in general it is well written and easy to read. also the length is sufficient for the topic. my three biggest concerns on the manuscripts are:? 1) by making multiple numbers boldface the focus is taken away from the best performing methods in each of the tables. 2) drawing run-time conclusions from comparing cpu algorithms to gpu algorithms is unfair and favors the gpu versions. 3) the comparison of the cascade: demosaick->classification and just the classification on the original seems to favor the demosaick->classification pipeline because images are greatly reduced in size anyway. 具体的意见就不放了，两个审稿人加起来提了13条左右的问题，包括让补充指定文献和书写错误之类的 发自小木虫Android客户端

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