AUTHOR=Pan Fei , Hu Mengdie , Duan Xuliang , Zhang Boda , Xiang Pengjun , Jia Lan , Zhao Xiaoyu , He Dawei TITLE=Enhancing kiwifruit flower pollination detection through frequency domain feature fusion: a novel approach to agricultural monitoring JOURNAL=Frontiers in Plant Science VOLUME=15 YEAR=2024 URL=https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2024.1415884 DOI=10.3389/fpls.2024.1415884 ISSN=1664-462X ABSTRACT=
The pollination process of kiwifruit flowers plays a crucial role in kiwifruit yield. Achieving accurate and rapid identification of the four stages of kiwifruit flowers is essential for enhancing pollination efficiency. In this study, to improve the efficiency of kiwifruit pollination, we propose a novel full-stage kiwifruit flower pollination detection algorithm named KIWI-YOLO, based on the fusion of frequency-domain features. Our algorithm leverages frequency-domain and spatial-domain information to improve recognition of contour-detailed features and integrates decision-making with contextual information. Additionally, we incorporate the Bi-Level Routing Attention (BRA) mechanism with C3 to enhance the algorithm’s focus on critical areas, resulting in accurate, lightweight, and fast detection. The algorithm achieves a