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October 2, 2025EAI endorsed transactions on intelligent systems and machine learning applications.Open Access

Hybrid Template Matching and Faster R-CNN for Robust Multimodal Object Detection

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Authors

HZHewa Majeed ZanganaDuhok Polytechnic University

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Implication

Hybrid approach enhances detection accuracy in occluded and cluttered environments, indicating improved robustness.

Key Points

  • The hybrid model achieves an F1 score of 88.6%, demonstrating significant robustness improvements.
  • Experimental results show a mAP@0.75 of 69.4%, surpassing both template-only and faster r-cnn-only models.
  • The inclusion of a fusion mechanism combines outputs from template matching and deep learning features effectively.
  • Robustness is notably improved in challenging conditions like occlusion and low resolution.

Cite This Study

Hewa Majeed Zangana (2025) studied this question.

synapsesocial.com/papers/68de68f683cbc991d0a21cf5https://doi.org/10.4108/eetismla.9544
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