Results 281 to 290 of about 107,458 (327)

TomatoPGT: A 3D point cloud dataset of tomato plants for segmentation and plant-trait extraction. [PDF]

Data Brief
Nethala P, Um D, McCoy SL, Gibson S, Bhandari M, Lee K.   +5 more
europepmc   +1 more source

DCSFormer: a high-precision method for cotton seedling point cloud organ segmentation. [PDF]

Front Plant Sci
Liu T, Sun W, Jiang H, Tian L, Jin C, Wang C, Cao J, Chen C, Hu F.   +8 more
europepmc   +1 more source

TeaNeRF: an integrated 3D visual perception pipeline for tea bud harvesting. [PDF]

Front Plant Sci
Chen W, Li X, Rao L, Xia X.
europepmc   +1 more source

Dual-Branch Point Cloud Semantic Segmentation: An EMA-Based Teacher-Student Collaborative Learning Framework. [PDF]

Sensors (Basel)
Zhang X, Hu Y, Li Y, Nan Z, Yu Q.
europepmc   +1 more source

MFPNet: A Semantic Segmentation Network for Regular Tunnel Point Clouds Based on Multi-Scale Feature Perception. [PDF]

Sensors (Basel)
Tong J, Ji M, Song P, Chen Q, Chen C.
europepmc   +1 more source

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Plane segmentation from point clouds

Pollack Periodica, 2018
Recently, attempts have been made to automate data acquisition, which is also related to efforts to automate data processing. The paper deals with the automation of terrestrial laser scanning data processing. The approaches for point cloud segmentation are briefly described.
Honti, Richard, Erdélyi, Ján, Kopáčik, Alojz   +2 more
openaire   +2 more sources

Interactive Learning for Point‐Cloud Motion Segmentation

Computer Graphics Forum, 2013
AbstractSegmenting a moving foreground (fg) from its background (bg) is a fundamental step in many Machine Vision and Computer Graphics applications. Nevertheless, hardly any attempts have been made to tackle this problem in dynamic 3D scanned scenes. Scanned dynamic scenes are typically challenging due to noise and large missing parts.
Yerry Sofer, Tal Hassner, Andrei Sharf
openaire   +1 more source

TLS point cloud segmentation based on points features

2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2017
This article proposes a point cloud segmentation method by merely relying on the spatial and echo characteristics of the point cloud of the terrestrial laser scanning (TLS). Firstly, terrain point cloud and off-terrain point cloud will be separated according to their own spatial characteristics. Then further segmentation to the terrain point cloud part
Jiang Hongbo, Jiao Qisong
openaire   +1 more source

Automated Sphere Segmentation from Point Clouds

Pollack Periodica, 2020
Nowadays huge datasets can be collected in a relatively short time. After capturing these data sets the next step is their processing. Automation of the processing steps can contribute to efficiency increase, to reduction of the time needed for processing, and to reduction of interactions of the user.
Honti, Richard, Erdélyi, Ján, Kopáčik, Alojz   +2 more
openaire   +2 more sources