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Dataset results
18 results for “Trunk segmentation”
GRIME AI Water Segmentation Model for the USGS Monitoring Site at East River at County Trunk HWY ZZ near Greenleaf, WI, 2023-2024
Ground-based observations from fixed-mount cameras have the potential to fill an important role in environmental sensing, including direct measurement of water levels and qualitative observation of ecohydrological research sites. All of this is theoretically possible for anyone who can install a trail camera. Easy acquisition of ground-based imagery has resulted in millions of environmental images stored, some of which are public data, and many of which contain information that has yet to be used for scientific purposes. The goal of this project was to develop and document key image processing and machine learning workflows, primarily related to semi-automated image labeling, to increase the use and value of existing and emerging archives of imagery that is relevant to ecohydrological processes. This data package includes imagery, annotation files, water segmentation model and model performance plots, and model test results (overlay images and masks) for USGS Monitoring Site at East River at County Trunk HWY ZZ near Greenleaf, WI. All imagery was acquired from the USGS Hydrologic Imagery Visualization and Information System (HIVIS; see https://apps.usgs.gov/hivis/camera/WI_East_River_at_HWY_ZZ_near_Greenleaf for this specific data set) and/or the National Imagery Management System (NIMS) API. Water segmentation models were created by tuning the open-source Segment Anything Model 2 (SAM2, https://github.com/facebookresearch/sam2) using images that were annotated by team members on this project. The models were trained on the "water" annotations, but annotation files may include additional labels, such as "snow", "sky", and "unknown". Image annotation was done in Computer Vision Annotation Tool (CVAT) and exported in COCO format (.json). All model training and testing was completed in GaugeCam Remote Image Manager Educational Artificial Intelligence (GRIME AI, https://gaugecam.org/) software (Version: Beta 16). Model performance plots were automatically generated duri
Vine Trunk Semantic Segmentation using Individual Vine Trunks
<p>Automatically labeled semantic segmentation dataset of vine trunk thumbnails extracted from VIneSet and other supplementary data.</p> <p>Source paper of this dataset is "Generating vine trunk semantic segmentation dataset via semi-supervised learning and object detection" published in MDPI Robotics https://www.mdpi.com/2218-6581/13/2/20.</p>
Dataset for image segmentation of tree trunks from depth maps captured with a an Android app using Google ARCore
<p>This dataset consists of pairs of depth maps created with a custom-built Android app using Google's ARCore for depth estimates, and tree trunk segments obtained from depth maps captured by Huawei''s AREngine and processed with a tree diameter estimation algorithm. This dataset was used for a machine learning segmentation task that aimed to improve the inputs from ARCore tree trunk depths to the tree diameter estimation algorithm. For each pair of depth maps and segments an RGB image of the scene where samples were captured is also included.</p>
FIGURE 15 in Variability in trunk segmentation in the centipede order Scolopendromorpha: a remarkable new species of Scolopendropsis Brandt (Chilopoda: Scolopendridae) from Brazil
FIGURE 15. South America, with dot indicating type locality of Scolopendropsis duplicata n. sp. (Brazil: Tocantins State: Porto Nacional). The distribution of S. bahiensis (Brandt, 1841) is indicated by black squares.
FIGURES 12–14. Scolopendropsis duplicata n in Variability in trunk segmentation in the centipede order Scolopendromorpha: a remarkable new species of Scolopendropsis Brandt (Chilopoda: Scolopendridae) from Brazil
FIGURES 12–14. Scolopendropsis duplicata n. sp. Paratype MNRJ 2392. 12, trunk segments 3–5, lateral view; 13, trunk segments 7–12, dorsal view; 14, trunk segments 7–11, ventral view. Scale bars, 1 mm.
FIGURES 6–11. Scolopendropsis duplicata n in Variability in trunk segmentation in the centipede order Scolopendromorpha: a remarkable new species of Scolopendropsis Brandt (Chilopoda: Scolopendridae) from Brazil
FIGURES 6–11. Scolopendropsis duplicata n. sp. Paratype MNRJ 2392. 6, cephalic plate and T1; 7, forcipular coxosternum; 8, segment 43 and ultimate legs, dorsal view; 9, segment 43 and ultimate legs, ventral view; 10, ultimate legs, dorsal view; 11, ultimate legs, ventral view. Scale bars, 1 mm.
FIGURES 2–5. Scolopendropsis duplicata n in Variability in trunk segmentation in the centipede order Scolopendromorpha: a remarkable new species of Scolopendropsis Brandt (Chilopoda: Scolopendridae) from Brazil
FIGURES 2–5. Scolopendropsis duplicata n. sp. Holotype MNRJ 15258. 2, forcipulae; 3, tooth plates (tp) and processes of trochanteroprefemora (pr) of forcipulae; 4, sternite and coxopleurae of segment 43; 5, segment 43 and ultimate legs, dorsal view. Scale bars, 0.5 mm. Additional abbreviations: dp, distomedial prefemoral process; ld, longitudinal depression on femur; ls, longitudinal sulcus delimiting pore field; sp, spine at posterior border of coxopleuron.
FIGURES 1, 2. Cylichnogaster lawrencei. Fig. 1. Partially enrolled male with 20 trunk segments. Fig. 2. Partially extended female with 23 in Redescription of the South African millipede Cylichnogaster lawrencei Verhoeff, 1937 and notes on the family Siphonotidae (Diplopoda, Polyzoniida)
FIGURES 1, 2. Cylichnogaster lawrencei. Fig. 1. Partially enrolled male with 20 trunk segments. Fig. 2. Partially extended female with 23 trunk segments.
Effect of Core Stability Training on Segmental Trunk Control and Quality of Life in Children with Cerebral Palsy
ClinicalTrials.gov study NCT06822296. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Data from: Absolute axial growth and trunk segmentation in the early Cambrian trilobite Oryctocarella duyunensis
Open the record for dataset details and reuse information.
FIGURE 1. Scolopendropsis duplicata n in Variability in trunk segmentation in the centipede order Scolopendromorpha: a remarkable new species of Scolopendropsis Brandt (Chilopoda: Scolopendridae) from Brazil
FIGURE 1. Scolopendropsis duplicata n. sp. Paratype MNRJ 15306. Lateral view. Scale bar, 1 mm.
DL models trained for multispectral tree trunk types detection and segmentation
<p>This repository holds Deep Learning (DL) models (YOLOv5 Small and YOLOv8 Small) that were trained to perform multispectral (4-channel RGB-NIR images) tree trunk types detection and segmentation in forested environments.</p>
Effects of Association of Trunk Stretching and Segmental Stabilization Exercises in Chronic Unspecific Low Back Pain
ClinicalTrials.gov study NCT02985892. IPD Sharing: NO. Countries: 1. Publications: 0.
Turkish Adaptation of Segmental Assessment of Trunk Control Scale
ClinicalTrials.gov study NCT04657276. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Segmental Trunk Stability Training on Sitting and Upper Limbs Functions in Children With Spastic Cerebral Palsy
ClinicalTrials.gov study NCT04937439. IPD Sharing: NO. Countries: 1. Publications: 0.
Cdx is crucial for the timing mechanism driving collinear Hox activation and defines a trunk segment in the Hox cluster topology
GEO Series GSE91046. Mus musculus. 3 samples. Type: Other.
ForTrunkSpecies - Image datasets of annotated RGB(-NIR) images for tree trunk types detection and segmentation at ground-level
<p>Two annotated image datasets for detection and segmentation of two tree trunk species - eucalyptus and pine:</p> <ul> <li>ForSpeciesDet(_4channels): dataset for tree trunk species detection in RGB(-NIR) images;</li> <li>ForSpeciesSeg(_4channels): dataset for tree trunk species segmentation in RGB(-NIR) images.</li> </ul>
The Relationship Between Segmental Trunk Control and Gross Motor Performance in Low Birth Weight Born Infant
ClinicalTrials.gov study NCT04313478. IPD Sharing: NO. Countries: 0. Publications: 0.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.