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[求助]
第一次投稿被拒，請(qǐng)高人幫看看編輯回信和審稿意見 已有6人參與
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問題：1.稿件按要求修改還可再投這家期刊嗎？ 2.稿件的問題很大嗎？再投其他刊物的可能性？審稿人說結(jié)論科學(xué)意義不大，還有必要繼續(xù)修改嗎？還是在選擇期看上有什么講究，是不是發(fā)表到好一點(diǎn)的會(huì)議上比較好，文章是一個(gè)新穎的初步探索，目前效果有，但是不是明顯。 謝謝！ 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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