ArticlePlant phenomics (Washington, D.C.)2021
Global Wheat Head Detection 2021: An Improved Dataset for Benchmarking Wheat Head Detection Methods.
Article in Plant phenomics (Washington, D.C.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.
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Who cites it
48 citing papers in PubMed.
- VT-SCC: Visual-text semantic alignment via multimodal guidance for unified staple crop organ counting.aBIOTECH · 2026Article
- ZCAT: Zero-shot cross-crop annotation transfer-A new paradigm leveraging plant organ similarity.Plant phenomics (Washington, D.C.) · 2026Article
- Deep learning in plant phenotyping: the first ten years.Plant phenomics (Washington, D.C.) · 2025Review
- The Global Wheat Full Semantic Organ Segmentation (GWFSS) dataset.Plant phenomics (Washington, D.C.) · 2025Article
- Global rice multiclass segmentation dataset (RiceSEG): comprehensive and diverse high-resolution RGB-annotated images for the development and benchmarking of rice segmentation algorithms.Plant phenomics (Washington, D.C.) · 2025Article
- RGB imaging and computer vision-based approaches for identifying spike number loci for wheat.Plant phenomics (Washington, D.C.) · 2025Article
- CVRP: A rice image dataset with high-quality annotations for image segmentation and plant phenomics research.Plant phenomics (Washington, D.C.) · 2025Article
- 3D-NOD: 3D new organ detection in plant growth by a spatiotemporal point cloud deep segmentation framework.Plant phenomics (Washington, D.C.) · 2025Article
- Multi-granularity alignment for crop diseases detection.Plant phenomics (Washington, D.C.) · 2025Article
- Research on detection and counting method of wheat ears in the field based on YOLOv11-EDS.Frontiers in plant science · 2025Article
- YOLOv8-FDA: lightweight wheat ear detection and counting in drone images based on improved YOLOv8.Frontiers in plant science · 2025Article
- Article
- Efficient Wheat Head Segmentation with Minimal Annotation: A Generative Approach.Journal of imaging · 2024Article
- PlantSR: Super-Resolution Improves Object Detection in Plant Images.Journal of imaging · 2024Article
- Oriented feature pyramid network for small and dense wheat heads detection and counting.Scientific reports · 2024Article
- Counting Canola: Toward Generalizable Aerial Plant Detection Models.Plant phenomics (Washington, D.C.) · 2024Article
- CSNet: A Count-Supervised Network via Multiscale MLP-Mixer for Wheat Ear Counting.Plant phenomics (Washington, D.C.) · 2024Article
- Feature diffusion reconstruction mechanism network for crop spike head detection.Frontiers in plant science · 2024Article
- A density map-based method for counting wheat ears.Frontiers in plant science · 2024Article
- Improved YOLO-FastestV2 wheat spike detection model based on a multi-stage attention mechanism with a LightFPN detection head.Frontiers in plant science · 2024Article
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Authors and funding
37 authors.
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Abstract
The Global Wheat Head Detection (GWHD) dataset was created in 2020 and has assembled 193,634 labelled wheat heads from 4700 RGB images acquired from various acquisition platforms and 7 countries/institutions. With an associated competition hosted in Kaggle, GWHD_2020 has successfully attracted attention from both the computer vision and agricultural science communities. From this first experience, a few avenues for improvements have been identified regarding data size, head diversity, and label reliability. To address these issues, the 2020 dataset has been reexamined, relabeled, and complemented by adding 1722 images from 5 additional countries, allowing for 81,553 additional wheat heads. We now release in 2021 a new version of the Global Wheat Head Detection dataset, which is bigger, more diverse, and less noisy than the GWHD_2020 version.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.