Objective:

To enhance the accuracy of gastrointestinal polyp detection through an improved YOLOv7 model.

Approach:

Key Findings:

• The improved YOLOv7 model achieved a precision of 94%.
• The recall rate was 88.7%.
• Mean average precision was 92.9%, showing improvement over the original model.

Interpretation:

The proposed YOLOv7 (EIoU + ECANet) model demonstrates strong robustness and generalization in detecting gastrointestinal polyps.

Conclusion:

The enhanced YOLOv7 model provides a more accurate and efficient method for gastrointestinal polyp detection.

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