7 citations · 8 across the 5 of their papers we have counts for
5 papers
PlantC2USeg: Cross-Scale Consistent Pre-Training for Few-Shot Unified Plant Point Cloud Segmentation
Yu Tian, Xintong Jiang, Jan Franklin Adamowski +2
Modern crop breeding demands precise organ-level analysis for trait quantification, making plant point cloud segmentation (PPCS) increasingly important. However, conventional deep…
Vision-Language Semantic Grounding for Multi-Domain Crop-Weed Segmentation
Nazia Hossain, Xintong Jiang, Yu Tian +3
Fine-grained crop-weed segmentation is essential for enabling targeted herbicide application in precision agriculture. However, existing deep learning models struggle to generalize…
Adapting SAM with Dynamic Similarity Graphs for Few-Shot Parameter-Efficient Small Dense Object Detection: A Case Study of Chickpea Pods in Field Conditions
Xintong Jiang, Yixue Liu, Mohamed Debbagh +4
Parameter-Efficient Fine-Tuning (PEFT) of foundation models for agricultural computer vision tasks remains challenging due to limited training data and complex field conditions. Th…
Predictive Modeling, Pattern Recognition, and Spatiotemporal Representations of Plant Growth in Simulated and Controlled Environments: A Comprehensive Review
Mohamed Debbagh, Shangpeng Sun, Mark Lefsrud
Accurate predictions and representations of plant growth patterns in simulated and controlled environments are important for addressing various challenges in plant phenomics resear…
Generative Plant Growth Simulation from Sequence-Informed Environmental Conditions
Mohamed Debbagh, Yixue Liu, Zhouzhou Zheng +3
A plant growth simulation can be characterized as a reconstructed visual representation of a plant or plant system. The phenotypic characteristics and plant structures are controll…