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第一次投稿被拒，请高人帮看看编辑回信和审稿意见 已有6人参与
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问题：1.稿件按要求修改还可再投这家期刊吗？ 2.稿件的问题很大吗？再投其他刊物的可能性？审稿人说结论科学意义不大，还有必要继续修改吗？还是在选择期看上有什么讲究，是不是发表到好一点的会议上比较好，文章是一个新颖的初步探索，目前效果有，但是不是明显。 谢谢！ Dear Dr. I have received the reviewers\' comments on your paper and regret that I cannot accept your manuscript for publication in the***. The reviewers\' comments about your paper are included below. Thank you for submitting your work to the ***. Sincerely, *** ----------------------------------- Reviewer comments: Reviewer #2 (Reviewer Comments Required): The idea flow of the paper can be improved. Suggest rewriting the paper in a natural way. Describe the entire system at the beginning and highlight the contribution clearly. For each part presented in paper, describe with clear definition, such as feature vector contents, how it is trained. Use better match symbol to represent the system. If it is referred from other place, point it out directly. Some figures do not match the caption and text. The experimental parts should compare with state-of-the-art methods to show its benefits. Reviewer #3 (Reviewer Comments Required): The paper proposes advanced tracking algorithm based on Hybrid Generative/Discriminative model, which is a combination of the two and with some additional features introduced (which is not clear enough). English in the paper should be considerably improved so that the sentences are more understandable. In the form as it is at the moment it is really difficult to follow the paper. Also structuring of the paper should be improved with additional diagrams to facilitate the paper reading. Results should be performed on more sequences and links for the sequences provided. Additionally, more state of the art algorithms (with references) should be used for comparison results. Processing time should not be provided for the MATLAB because it gives very little information about the processing load and the speed of the algorithm. If you want to make statements on that please describe the load for the block, memory access, etc. Reviewer #4 (Reviewer Comments Required): The authors tried to present a so called hybrid object tracking algorithm by combining Fisher LDA and PCA. Harr-like features are used for training and appearance model updating purposes. However, the algorithm is poorly presented, and the experiments are too weak and with minor scientific merit. There are lots of language errors in the paper, and the organization of the paper is not clear too. Language needs to be significantly improved. Detailed commends are as below: *** |
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