Sri Wahjuni
Papers
1
Total Citations
8
H-Index
1
About
Sri Wahjuni’s research bridges computer vision and agricultural robotics, with a focus on enabling intelligent plant care. Her key contributions center on leaf segmentation and depth-aware image processing for precision pruning. In her highly cited 2023 work, “Faster RCNN based leaf segmentation using stereo images,” she developed a deep learning framework that uses aligned RGB-Depth images to distinguish leaves from branches in golden melon plants—a critical step for robotic pruning. This approach, which has garnered 8 citations, demonstrates how Faster R-CNN can be adapted for agricultural tasks, improving plant metabolism through automated, efficient pruning. Her work addresses a practical bottleneck in greenhouse automation, where robots must accurately identify plant structures in complex, real-world settings. By integrating stereo vision with convolutional neural networks, Wahjuni has advanced the field of precision agriculture, offering scalable solutions for crop management. Her research not only highlights the potential of computer vision in horticulture but also sets a foundation for future work in robotic plant interaction, making her a notable contributor to the intersection of AI and sustainable farming.
Research Focus
Key Achievements
Top Papers
- 1Faster RCNN based leaf segmentation using stereo images8 citations · 2023