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The study aims to enhance the performance of object detection in rice fields for robot combines using deep learning methods.

Improvement of object detection in rice field environment with a fisheye-lens camera for robot combine based on a guided training method

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The study aims to enhance the performance of object detection in rice fields for robot combines using deep learning methods.
Utilized two deep neural networks: FCNResNet50 and FCNVGG16.
Deployed a fisheye-lens camera for wider image capture.
Trained models using cropped images from specific areas in the dataset.
FCNResNet50 showed 1–5% improvement in performance.
FCNVGG16 exhibited a 10% average increase in detection capabilities.
Mean intersection over union, pixel accuracy, and class accuracy improved significantly.

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Improves object detection in rice fields using a fisheye-lens camera, indicating enhanced robotic harvesting capabilities.

CHEN et al. (2026) studied this question.

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