12 citations · 25 across the 15 of their papers we have counts for
15 papers
EvoTSC: Evolving Feature Learning Models for Time Series Classification via Genetic Programming
Xuanhao Yang, Bing Xue, Mengjie Zhang
Time series classification is an important analytical task across diverse domains. However, its practical application is often hindered by the scarcity of labeled data and the requ…
Positioning radiata pine branches requiring pruning by drone stereo vision
Yida Lin, Bing Xue, Mengjie Zhang +2
This paper presents a stereo-vision-based system mounted on a drone for detecting and localising radiata pine branches to support autonomous pruning. The proposed pipeline comprise…
Enhancing Generalization in Evolutionary Feature Construction for Symbolic Regression through Vicinal Jensen Gap Minimization
Hengzhe Zhang, Qi Chen, Bing Xue +2
Genetic programming-based feature construction has achieved significant success in recent years as an automated machine learning technique to enhance learning performance. However,…
Performance Evaluation of Deep Learning for Tree Branch Segmentation in Autonomous Forestry Systems
Yida Lin, Bing Xue, Mengjie Zhang +2
UAV-based autonomous forestry operations require rapid and precise tree branch segmentation for safe navigation and automated pruning across varying pixel resolutions and operation…
YOLO and SGBM Integration for Autonomous Tree Branch Detection and Depth Estimation in Radiata Pine Pruning Applications
Yida Lin, Bing Xue, Mengjie Zhang +2
Manual pruning of radiata pine trees poses significant safety risks due to extreme working heights and challenging terrain. This paper presents a computer vision framework that int…
Genetic Algorithms For Parameter Optimization for Disparity Map Generation of Radiata Pine Branch Images
Yida Lin, Bing Xue, Mengjie Zhang +2
Traditional stereo matching algorithms like Semi-Global Block Matching (SGBM) with Weighted Least Squares (WLS) filtering offer speed advantages over neural networks for UAV applic…
Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys
Mitchell Rogers, Theo Thompson, Isla Duporge +5
Recent advancements in deep learning and aerial imaging have transformed wildlife monitoring, enabling researchers to survey wildlife populations at unprecedented scales. Unmanned…
A Genetic Algorithm-Based Approach for Automated Optimization of Kolmogorov-Arnold Networks in Classification Tasks
Quan Long, Bin Wang, Bing Xue +1
To address the issue of interpretability in multilayer perceptrons (MLPs), Kolmogorov-Arnold Networks (KANs) are introduced in 2024. However, optimizing KAN structures is labor-int…
EvoSampling: A Granular Ball-based Evolutionary Hybrid Sampling with Knowledge Transfer for Imbalanced Learning
Wenbin Pei, Ruohao Dai, Bing Xue +4
Class imbalance would lead to biased classifiers that favor the majority class and disadvantage the minority class. Unfortunately, from a practical perspective, the minority class…
Drone Stereo Vision for Radiata Pine Branch Detection and Distance Measurement: Utilizing Deep Learning and YOLO Integration
Yida Lin, Bing Xue, Mengjie Zhang +2
This research focuses on the development of a drone equipped with pruning tools and a stereo vision camera to accurately detect and measure the spatial positions of tree branches.…
Drone Stereo Vision for Radiata Pine Branch Detection and Distance Measurement: Integrating SGBM and Segmentation Models
Yida Lin, Bing Xue, Mengjie Zhang +2
Manual pruning of radiata pine trees presents significant safety risks due to their substantial height and the challenging terrains in which they thrive. To address these risks, th…
Sharpness-Aware Minimization for Evolutionary Feature Construction in Regression
Hengzhe Zhang, Qi Chen, Bing Xue +2
In recent years, genetic programming (GP)-based evolutionary feature construction has achieved significant success. However, a primary challenge with evolutionary feature construct…
A Consistent Lebesgue Measure for Multi-label Learning
Kaan Demir, Bach Nguyen, Bing Xue +1
Multi-label loss functions are usually non-differentiable, requiring surrogate loss functions for gradient-based optimisation. The consistency of surrogate loss functions is not pr…
Improving Buoy Detection with Deep Transfer Learning for Mussel Farm Automation
Carl McMillan, Junhong Zhao, Bing Xue +2
The aquaculture sector in New Zealand is experiencing rapid expansion, with a particular emphasis on mussel exports. As the demands of mussel farming operations continue to evolve,…
Generating Redundant Features with Unsupervised Multi-Tree Genetic Programming
Andrew Lensen, Bing Xue, Mengjie Zhang
Recently, feature selection has become an increasingly important area of research due to the surge in high-dimensional datasets in all areas of modern life. A plethora of feature s…