Tiantian Ji
Papers
1
Total Citations
4
H-Index
1
About
Tiantian Ji is a researcher at the forefront of agricultural technology, specializing in computer vision, deep learning, and embedded systems for precision pest monitoring. Her work addresses the critical challenge of real-time crop protection by developing lightweight, deployable detection models. Ji’s most notable contribution is the creation of RSCDet, a novel, efficient deep learning architecture designed specifically for aphid detection in cereal crops. This model achieves high accuracy while being compact enough for deployment on low-cost, portable embedded devices like the NVIDIA Jetson TX2 NX. By integrating RSCDet into a complete system platform, Ji has demonstrated a practical, scalable solution for real-time pest monitoring in the field, moving beyond theoretical models to tangible agricultural tools. Her work, published in 2025 and already garnering citations, represents a significant step toward accessible, AI-driven pest management. Ji’s research directly impacts sustainable agriculture by enabling farmers to detect infestations early and precisely, reducing reliance on broad-spectrum pesticides. Her focus on bridging advanced deep learning with real-world, resource-constrained deployment marks her as an innovator in smart farming technology.
Research Focus
Key Achievements
Top Papers
- 1