Presentation

Does the manuscript present a cohesive argument? Are the ideas clearly and logically organized?

Writing

Does the title accurately characterize the manuscript? Is the writing concise, precise, and easy to follow?

Length

Which parts of the manuscript should be expanded, removed, condensed, summarized, or combined to improve clarity and contribution?

Title

Is the title concise and informative, omitting unnecessary terms and, where possible, stating the main result, method, or contribution? Are abbreviations avoided in the title?

Abstract

Does the abstract include: (1) aim/purpose of the study; (2) method or proposed approach; (3) key results/findings; and (4) conclusion/implications?

Introduction

Does the introduction clearly describe:

• The background and significance of the study;
• State of the art and relevant prior research in deep learning, computer vision, digital image processing, or related fields;
• Gap analysis and a clear novelty statement;
• Research questions, objectives, or hypotheses where relevant;
• The proposed approach, model, framework, or technique used to address the problem; and
• The aim/objectives of the study.

Method

• Is the method described clearly enough for replication and evaluation?
• Does the section explain how the research was conducted, rather than only defining concepts?
• Are the dataset, data source, preprocessing steps, model architecture, experimental setup, parameters, tools, and evaluation procedures clearly stated?
• For deep learning or computer vision studies: are training, validation, testing, augmentation, optimization, hyperparameters, and hardware/software environments reported appropriately?
• Are the evaluation metrics, such as accuracy, precision, recall, F1-score, mAP, IoU, PSNR, SSIM, or other relevant metrics, clearly explained and justified?

Results and Discussion

• Are results presented as processed data, using appropriate tables, figures, graphs, confusion matrices, sample outputs, or visual comparisons?
• Do the results address the research objectives stated in the Introduction?
• Are findings compared with relevant prior studies, baseline models, or existing methods?
• Does the manuscript provide scientifically grounded interpretations for each key finding?
• Are model performance, strengths, limitations, computational efficiency, and practical relevance discussed clearly?
• Are limitations and potential threats to validity, such as dataset size, class imbalance, overfitting, generalizability, or bias, clearly acknowledged?
• Does the paper identify future research directions or opportunities for improving the proposed method?

Conclusion

Does the conclusion:

• Directly answer the objectives of the research;
• Summarize the main findings without repeating excessive numerical details;
• Provide implications and/or recommendations where appropriate;
• Appear as a paragraph, not bullet points or numbering?

Scope Fit for DECODING

Does the manuscript clearly relate to deep learning, computer vision, digital image processing, pattern recognition, image classification, object detection, image segmentation, medical image analysis, remote sensing image processing, video analysis, visual computing, or related artificial intelligence applications involving image or visual data?