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Paper has been improved and now acceptable for publication.
[# PeerJ Staff Note - this decision was reviewed and approved by Jyotismita Chaki, a PeerJ Section Editor covering this Section #]
All of my concerns are addressed adequately, so I do not have any further comments. I would recommend acceptance of the article in the current state.
well defined
Clearly stated and executed
NA
Clear the contributions of work. Address all the comments of reviewers.
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The paper titled "Recognition of Inscribed Cursive Pashtu Numeral Through Optimized Deep Learning" endeavors to introduce a deep learning methodology for the identification of Pashtu numerals ranging from 0 to 9. While the paper appears promising, yet certain concerns have also been raised for the authors to address.
• Mention the characteristics of the dataset, such as the diversity of handwriting styles, or any data quality issues, etc. for assessing the generalizability and reliability of the proposed model.
• A brief rational explanation for the necessity of data reshaping is required to enhance clarity for readers unfamiliar with the technical aspects of these architectures.
• The introduction uses terms like "Pashtu" and "Pashto" interchangeably. Ensuring consistency in terminology will contribute to a clearer and more professional presentation of the research.
• The article should remove the grammatical mistakes. Please proofread paper for small grammatical mistakes and such as using capital letter in the middle of the sentences.
• The article requires overall improvements in English language usage and flow.
• I would recommend acceptance upon addressing these issues and enhancing the clarity and coherence of the article.
• Mention the characteristics of the dataset, such as the diversity of handwriting styles, or any data quality issues, etc. for assessing the generalizability and reliability of the proposed model.
• A brief rational explanation for the necessity of data reshaping is required to enhance clarity for readers unfamiliar with the technical aspects of these architectures.
• The results and discussion section lacks analysis and details. Add implication of your results too.
• The introduction uses terms like "Pashtu" and "Pashto" interchangeably. Ensuring consistency in terminology will contribute to a clearer and more professional presentation of the research.
• Formatting of Table 1 and Table 2 is different. Please use the right formatting according to the journal.
This paper proposes a CNN and LSTM based model to classify pashtu handwritten words, This problem looks important since there has been very less work pashto language. However, the paper need much more improvements;
I don't see the contribution of the paper is comprehensively described? It is better to explain in more detail. such as you say CNN and LSTM models are used. However, this not a contribution, the point is what modification you made to lstm and CNN for your application. need to explain in a little more detail.
too many typos and awkward mistake in throughout the manuscript such as after eq. 1 .....where Vinput... what is Vinput?
what is the question mark before equation 3 .... after applying zero-padding to the image
is as shown in equation 2 ?..... the title of subsection image Processing? ...........the question mark before equation 11......
it sounds like the authors created their own dataset right? if i am not missing something this could be considered as your contribution.
the recall and precision formulas are quite strange. why don't you use TP,TNFPFN for both formulas
nn
nn
nn
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