datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
lgg-mri-segmentation-research
LGG Brain MRI Segmentation with Genomic Clusters
This repository provides a Patient-Centric version of the Lower-Grade Glioma (LGG) Segmentation dataset. While other versions of this data exist, they often treat slices as independent images. This version preserves the 3D patient volume and integrates all genomic/clinical labels directly into a multimodal-ready format.
🌟 Why This Version?
Developed for Multimodal AI Research, this dataset addresses several limitations… See the full description on the dataset page: https://huggingface.co/datasets/Ehsan-rmz/lgg-mri-segmentation-research.lgg-mri-segmentation-research
LGG Brain MRI Segmentation with Genomic Clusters
This repository provides a Patient-Centric version of the Lower-Grade Glioma (LGG) Segmentation dataset. While other versions of this data exist, they often treat slices as independent images. This version preserves the 3D patient volume and integrates all genomic/clinical labels directly into a multimodal-ready format.
🌟 Why This Version?
Developed for Multimodal AI Research, this dataset addresses several limitations… See the full description on the dataset page: https://huggingface.co/datasets/vpasx/lgg-mri-segmentation-research.fruitseg30_segmentation
FruitSeg30 Segmentation
A dataset for semantic segmentation of common types of fruit in a lab environment. The dataset contains 1,969 images with pixel-level mask annotations.
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@article{shamrat2024fruitseg30_segmentation,
title={FruitSeg30\_Segmentation dataset \& mask annotations: A novel dataset for diverse fruit segmentation and classification}… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/fruitseg30_segmentation.cocoa_tree_point_cloud_segmented
Cocoa Tree Point Cloud Segmented
This dataset provides real LiDAR point cloud data of cocoa trees in a field environment in Cameroon, collected for crop segmentation applications within agroforestry systems. Captured using a ground-based Leica ScanStation C10 during August 2019, it delivers high-resolution structural information of cocoa tree canopies for agricultural monitoring research. The dataset contains 85 images across 3 classes: full, leaf, wood.Images per class:
full:… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/cocoa_tree_point_cloud_segmented.