Results 281 to 290 of about 1,465,159 (304)

Evaluating Segmentation Quality via Reference Segmentations in Tree-like Structure

2019 IEEE 14th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), 2019
In the image segmentation task, different understandings of the image content will lead to different granularities of segmentation results. Existing segmentation evaluation methods generally use one or more reference segmentations to evaluate the quality of image segmentation.
Chao Wang, Bo Peng 0006, Xun Gong 0002, Zeng Yu 0001, Tianrui Li 0001   +4 more
openaire   +1 more source

Automatic Segmentation by Decision Trees

1996
We present a system for automatic segmentation by decision trees, able to cope with large data sets, with special attention to stability problems. Tree-based methods are a statistical operation for automatic learning from data, its main characteristic is the simplicity of the obtained results.
Tomàs Aluja-Banet, Eduard Nafria
openaire   +1 more source

Segmentation of Forest to Tree Objects

2013
This chapter reviews the use of airborne LiDAR data for the segmentation of forest to tree objects. The benefit obtained by LiDAR data is typically related to the use of the third dimension, i.e. the height data. Forest and stand objects may be segmented based on physical criteria, for example height and density information, while a further delineation
Koch, Barbara, Kattenborn, Teja, Straub, Christoph, Vauhkonen, Jari   +3 more
openaire   +2 more sources

Convolutional Decision Trees for Feature Learning and Segmentation

2014
Most computer vision and especially segmentation tasks require to extract features that represent local appearance of patches. Relevant features can be further processed by learning algorithms to infer posterior probabilities that pixels belong to an object of interest.
Dmitry Laptev, Joachim M. Buhmann
openaire   +1 more source

Skin Lesion Segmentation Using Adaptive Color Segmentation and Decision Tree

Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications
A decision tree operates as a predictive model in machine learning, utilizing a structured hierarchy of rules for the decision-making process. This model is graphically depicted through a tree-like structure, where each node symbolizes a decision point, and the ensuing branches represent the resultant outcomes of these decisions.
Arief Kelik Nugroho, Afiah ayati, Moh Edi Wibowo, Hardyanto Soebono, Retantyo Wardoyo   +4 more
openaire   +1 more source

Study on Individual Tree Segmentation of Different Tree Species Using Different Segmentation Algorithms Based on 3D UAV Data

Forests, 2023
Haotian You, Xu Tang, Qixu You
exaly  

Individual tree segmentation and tree species classification in subtropical broadleaf forests using UAV-based LiDAR, hyperspectral, and ultrahigh-resolution RGB data

Remote Sensing of Environment, 2022
Haiming Qin, Weiqi Zhou
exaly  

Urban street tree dataset for image classification and instance segmentation

Computers and Electronics in Agriculture, 2023
Ting-ting YANG, Aijun Xu, Suyin Zhou
exaly  

Benchmarking airborne laser scanning tree segmentation algorithms in broadleaf forests shows high accuracy only for canopy trees

International Journal of Applied Earth Observation and Geoinformation, 2023
Nikolai Knapp, Toby Jackson, James G C Ball   +2 more
exaly  

The Semantic Segmentation of Standing Tree Images Based on the Yolo V7 Deep Learning Algorithm

Electronics, 2023
Lianjun Cao
exaly