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Random forests are widely used in regression. However, the decision trees used as base learners are poor approximators of linear relationships. To address this limitation we propose RaFFLE (Random Forest Featuring Linear Extensions), a…

Machine Learning · Computer Science 2025-02-17 Jakob Raymaekers , Peter J. Rousseeuw , Thomas Servotte , Tim Verdonck , Ruicong Yao

Tree-based models are often robust to uninformative features and can accurately capture non-smooth, complex decision boundaries. Consequently, they often outperform neural network-based models on tabular datasets at a significantly lower…

Machine Learning · Computer Science 2025-05-08 Urška Matjašec , Nikola Simidjievski , Mateja Jamnik

The width measure \emph{treedepth}, also known as vertex ranking, centered coloring and elimination tree height, is a well-established notion which has recently seen a resurgence of interest. We present an algorithm which---given as input…

Data Structures and Algorithms · Computer Science 2014-08-21 Felix Reidl , Peter Rossmanith , Fernando Sanchez Villaamil , Somnath Sikdar

A Robotic Mobile Fulfillment System is a robotised parts-to-picker system that is particularly well-suited for e-commerce warehousing. One distinguishing feature of this type of warehouse is its high storage modularity. Numerous robots are…

Robotic harvesting of fruits in orchards is a challenging task, since high density and overlapping of fruits and branches can heavily impact the success rate of robotic harvesting. Therefore, the vision system is demanded to provide…

Computer Vision and Pattern Recognition · Computer Science 2021-12-09 Hanwen Kang , Chao Chen

Accurate tree height estimation is vital for ecological monitoring and biomass assessment. We apply quantile regression to existing tree height estimation models based on satellite data to incorporate uncertainty quantification. Most…

Computer Vision and Pattern Recognition · Computer Science 2026-04-09 Karsten Schrödter , Jan Pauls , Fabian Gieseke

Reliable large-scale data on the state of forests is crucial for monitoring ecosystem health, carbon stock, and the impact of climate change. Current knowledge of tree species distribution relies heavily on manual data collection in the…

Computer Vision and Pattern Recognition · Computer Science 2024-12-09 Hongjin Lin , Matthew Nazari , Derek Zheng

Autonomous navigation in unstructured vegetated environments remains an open challenge. To successfully operate in these settings, ground vehicles must assess the traversability of the environment and determine which vegetation is pliable…

Robotics · Computer Science 2024-05-16 Fabio Ruetz , Nicholas Lawrance , Emili Hernández , Paulo Borges , Thierry Peynot

Tree ensembles such as random forests and boosted trees are accurate but difficult to understand, debug and deploy. In this work, we provide the inTrees (interpretable trees) framework that extracts, measures, prunes and selects rules from…

Machine Learning · Computer Science 2014-08-26 Houtao Deng

Bone age is an important measure for assessing the skeletal and biological maturity of children. Delayed or increased bone age is a serious concern for pediatricians, and needs to be accurately assessed in a bid to determine whether bone…

Computer Vision and Pattern Recognition · Computer Science 2021-04-19 Ibrahim Salim , A. Ben Hamza

Generating accurate digital tree models from scanned environments is invaluable for forestry, agriculture, and other outdoor industries in tasks such as identifying biomass, fall hazards and traversability, as well as digital applications…

Computer Vision and Pattern Recognition · Computer Science 2023-03-03 Thomas Lowe , Joshua Pinskier

Sampling-based motion planning has emerged as a powerful approach for robotics, enabling exploration of complex, high-dimensional configuration spaces. When combined with Signal Temporal Logic (STL), a temporal logic widely used for…

Robotics · Computer Science 2026-02-20 Ahmad Ahmad , Shuo Liu , Roberto Tron , Calin Belta

We formalize and enable the task of open tree decomposition, which segments an image into hierarchical trees of visual components with unconstrained granularity and flexibility. Specifically, we provide the foundation benchmark for this new…

Computer Vision and Pattern Recognition · Computer Science 2026-05-22 Junhyub Lee , Seunghun Chae , Hyosu Kim

Accurate localization is an important functional requirement for precision orchard management. However, there are few off-the-shelf commercial solutions available to growers. In this paper, we present SeeTree, a modular, open source…

Computer Vision and Pattern Recognition · Computer Science 2025-04-16 Jostan Brown , Cindy Grimm , Joseph R. Davidson

Global food production depends upon successful pollination, a process that relies on natural and managed pollinators. However, natural pollinators are declining due to factors such as climate change, habitat loss, and pesticide use. This…

Random forest (RF) stands out as a highly favored machine learning approach for classification problems. The effectiveness of RF hinges on two key factors: the accuracy of individual trees and the diversity among them. In this study, we…

Machine Learning · Computer Science 2024-10-28 Ye-eun Kim , Seoung Yun Kim , Hyunjoong Kim

Treemaps have been widely applied to the visualization of hierarchical data. A treemap takes a weighted tree and visualizes its leaves in a nested planar geometric shape, with sub-regions partitioned such that each sub-region has an area…

Graphics · Computer Science 2023-09-01 Mehdi Behroozi , Reyhaneh Mohammadi , Cody Dunne

Harvesting is a critical task in the tree fruit industry, demanding extensive manual labor and substantial costs, and exposing workers to potential hazards. Recent advances in automated harvesting offer a promising solution by enabling…

Computer Vision and Pattern Recognition · Computer Science 2025-06-09 Keyi Zhu , Jiajia Li , Kaixiang Zhang , Chaaran Arunachalam , Siddhartha Bhattacharya , Renfu Lu , Zhaojian Li

Contact-rich manipulation tasks in agriculture, such as pruning and harvesting, require robots to physically interact with tree structures to maneuver through cluttered foliage. Identifying whether the robot is contacting rigid or soft…

Robotics · Computer Science 2025-05-20 Ryan Spears , Moonyoung Lee , George Kantor , Oliver Kroemer

Recognizing 3D objects in the presence of noise, varying mesh resolution, occlusion and clutter is a very challenging task. This paper presents a novel method named Rotational Projection Statistics (RoPS). It has three major modules: Local…

Computer Vision and Pattern Recognition · Computer Science 2013-04-12 Yulan Guo , Ferdous Sohel , Mohammed Bennamoun , Min Lu , Jianwei Wan