2026· International Conference on Conceptual Structures· pp. 566-573· 0 citations· 11 references
Computer Science
TL;DR
The experimental re-sults demonstrate the feasibility of deploying advanced computer vision models on embedded platforms for agricultural applications, enabling autonomous crop detection and harvesting assistance in controlled indoor conditions, representing a first step toward real-world field deployment.
Weeds create a significant challenge in agricultural production by competing with crops for essential resources such as nutrients, sunlight, and water. This competition leads to reduced crop yields and quality, resulting in substantial economic losses. Consequently, there is a critical need for effective weed control s...
Najia Ait Hammou, Abdellah El Aissaoui, Yassine Abouch et al.· AgriEngineering· 0 citations
To develop an edge-deployable greenhouse tomato cluster harvesting robot capable of accurate fruit detection, three-dimensional localization, autonomous navigation, and robotic harvesting under complex greenhouse conditions. The objective was to improve detection performance under fruit occlusion and variable illum...
Fan-Zhao Meng, Zhen Wang, Huan Wang et al.· Frontiers in Plant Science· 0 citations
In addressing the high labor costs and low operational efficiency of greenhouse tomato harvesting and separate packaging workflows, this study develops an integrated tomato harvesting robotic system embedded with RGB-D machine vision, 5-degree-of-freedom manipulator and vertical heat-sealing net bag packaging mechanism...
Yan-Hua Ying, Dongya Li, Jia-Hui Hu et al.· INMATEH Agricultural Enginee...· 0 citations
The key novelty of HarvestMate lies in its end-to-end autonomous harvesting cycle on a single low-cost embedded platform, and an efficient, platform-specific optimization using a precomputed reachability matrix, addressing an accessibility gap for small-scale indoor growers currently unserved by commercial solutions.
Ali A. El-Moursy, Wafa Al-Kathiri, Maram Al-Jayyosi et al.· Journal of Circuits, Systems...· 0 citations
Insect pollination is critical for global food production, yet monitoring pollinators at commercial farm scale remains a challenge. Recent advances in computer vision and deep learning have enabled detailed analysis of pollinator behaviour, but monitoring must trade-off detail against spatial coverage and human or tech...
Malika Nisal Ratnayake, A. N. Toosi, James Cook et al.· 0 citations
Orchard production involves intensive labor requirements, limited operational periods, and highly dynamic and complex working environments. Consequently, the development of intelligent orchard robots has become a important approach to enhancing production efficiency and reducing reliance on manual operations. This revi...
Rui Ye, Mingxiong Ou· Applied Sciences· 0 citations
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