ArticlePlant phenomics (Washington, D.C.)2021
Deep Multiview Image Fusion for Soybean Yield Estimation in Breeding Applications.
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 23 papers.
What it found
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The trial behind it
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Who cites it
23 citing papers in PubMed.
- High-density field-based 3D reconstruction of rice architecture across diverse cultivars for genome-wide association studies.Plant methods · 2026Article
- Amodal Segmentation and Trait Extraction of On-Branch Soybean Pods with a Synthetic Dual-Mask Dataset.Sensors (Basel, Switzerland) · 2025Article
- PodNet: Pod real-time instance segmentation in pre-harvest soybean fields.Plant phenomics (Washington, D.C.) · 2025Article
- DLML-PC: an automated deep learning and metric learning approach for precise soybean pod classification and counting in intact plants.Frontiers in plant science · 2025Article
- Robust soybean seed yield estimation using high-throughput ground robot videos.Frontiers in plant science · 2025Article
- Harnessing Multi-Omics Strategies and Bioinformatics Innovations for Advancing Soybean Improvement: A Comprehensive Review.Plants (Basel, Switzerland) · 2024Review
- Persistent monitoring of insect-pests on sticky traps through hierarchical transfer learning and slicing-aided hyper inference.Frontiers in plant science · 2024Article
- DEKR-SPrior: An Efficient Bottom-Up Keypoint Detection Model for Accurate Pod Phenotyping in Soybean.Plant phenomics (Washington, D.C.) · 2024Article
- Segmentation and Phenotype Calculation of Rapeseed Pods Based on YOLO v8 and Mask R-Convolution Neural Networks.Plants (Basel, Switzerland) · 2023Article
- A Novel Approach to Pod Count Estimation Using a Depth Camera in Support of Soybean Breeding Applications.Sensors (Basel, Switzerland) · 2023Article
- YOLO POD: a fast and accurate multi-task model for dense Soybean Pod counting.Plant methods · 2023Article
- A Multiscale Point-Supervised Network for Counting Maize Tassels in the Wild.Plant phenomics (Washington, D.C.) · 2023Article
- "Canopy fingerprints" for characterizing three-dimensional point cloud data of soybean canopies.Frontiers in plant science · 2023Article
- Improved Field-Based Soybean Seed Counting and Localization with Feature Level Considered.Plant phenomics (Washington, D.C.) · 2023Article
- Multi-Omics Techniques for Soybean Molecular Breeding.International journal of molecular sciences · 2022Review
- High-throughput field crop phenotyping: current status and challenges.Breeding science · 2022Article
- Exploring Soybean Flower and Pod Variation Patterns During Reproductive Period Based on Fusion Deep Learning.Frontiers in plant science · 2022Article
- Deep learning-based phenotyping for genome wide association studies of sudden death syndrome in soybean.Frontiers in plant science · 2022Article
- Soybean Yield Formation Physiology - A Foundation for Precision Breeding Based Improvement.Frontiers in plant science · 2021Review
- Global Wheat Head Detection 2021: An Improved Dataset for Benchmarking Wheat Head Detection Methods.Plant phenomics (Washington, D.C.) · 2021Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Reliable seed yield estimation is an indispensable step in plant breeding programs geared towards cultivar development in major row crops. The objective of this study is to develop a machine learning (ML) approach adept at soybean (
Identifiers
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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.