Chenjiao Tan
Papers
3
Total Citations
29
H-Index
2
About
Chenjiao Tan is a researcher at the forefront of agricultural computer vision, specializing in automated plant phenotyping for cotton crops. Her work centers on developing sophisticated multi-object tracking and multi-modal imaging techniques to solve the critical challenge of in-field yield estimation. Tan’s major contributions include pioneering methods for counting cotton flowers and bolls—key indicators of reproductive growth and final yield—directly from ground-based video and RGB-D imagery. Her most cited work, a 2024 study on three-view cotton flower counting, has already garnered 24 citations, highlighting its immediate impact on the field. This research, along with her subsequent work on transformer-based models for boll counting, provides breeders and growers with non-destructive, high-throughput tools to assess genotype productivity and make informed crop management decisions. By translating complex computer vision models into practical agricultural solutions, Tan is helping to bridge the gap between genomic data and field performance, ultimately supporting the development of more resilient and productive cotton varieties.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3