10 papers
Benchmarking Zero-Shot LLM-Generated Parent Selection in Genetic Programming for Symbolic Regression
Hengzhe Zhang, Qi Chen, Bing Xue +2
Parent selection significantly affects exploration, exploitation, and complexity control in genetic programming (GP) for symbolic regression. It is unclear whether large language m…
Neural Architecture Distributions: A New Paradigm for Stochastic Segmentation
Conghui Li, Junhao Huang, Chern Hong Lim +2
Stochastic segmentation seeks to represent multiple plausible masks for a single image, which is essential in safety- and quality-critical applications such as medical imaging or b…
Low-Cost Stereo Vision for Robust 3D Positioning of Thin Radiata Pine Branches in Autonomous Drone Pruning
Yida Lin, Bing Xue, Mengjie Zhang +2
Manual pruning of radiata pine, a species of major economic importance to New Zealand forestry, is hazardous, labour-intensive, and increasingly constrained by workforce shortages.…
LLM-Meta-SR: In-Context Learning for Evolving Selection Operators in Symbolic Regression
Hengzhe Zhang, Qi Chen, Bing Xue +2
Large language models (LLMs) have revolutionized algorithm development, yet their application in symbolic regression, where algorithms automatically discover symbolic expressions f…
UE5-Forest: A Photorealistic Synthetic Stereo Dataset for UAV Forestry Depth Estimation
Yida Lin, Bing Xue, Mengjie Zhang +2
Dense ground-truth disparity maps are practically unobtainable in forestry environments, where thin overlapping branches and complex canopy geometry defeat conventional depth senso…
Towards Gold-Standard Depth Estimation for Tree Branches in UAV Forestry: Benchmarking Deep Stereo Matching Methods
Yida Lin, Bing Xue, Mengjie Zhang +2
Autonomous UAV forestry operations require robust depth estimation with strong cross-domain generalization, yet existing evaluations focus on urban and indoor scenarios, leaving a…