Deep learning: as the new frontier in high-throughput plant phenotyping
Published 2022 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Deep learning: as the new frontier in high-throughput plant phenotyping
Authors
Keywords
-
Journal
EUPHYTICA
Volume 218, Issue 4, Pages -
Publisher
Springer Science and Business Media LLC
Online
2022-03-18
DOI
10.1007/s10681-022-02992-3
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Deep Learning for Predicting Complex Traits in Spring Wheat Breeding Program
- (2021) Karansher S. Sandhu et al. Frontiers in Plant Science
- Combining Genomic and Phenomic Information for Predicting Grain Protein Content and Grain Yield in Spring Wheat
- (2021) Karansher S. Sandhu et al. Frontiers in Plant Science
- Deep learning for classification and severity estimation of coffee leaf biotic stress
- (2020) José G.M. Esgario et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Deep learning based segmentation for automated training of apple trees on trellis wires
- (2020) Yaqoob Majeed et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Recent advances in deep learning
- (2020) Xizhao Wang et al. International Journal of Machine Learning and Cybernetics
- Sparse Convolutional Neural Networks for Genome-Wide Prediction
- (2020) Patrik Waldmann et al. Frontiers in Genetics
- Aerial hyperspectral imagery and deep neural networks for high-throughput yield phenotyping in wheat
- (2020) Ali Moghimi et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Genome-wide association study reveals the genetic basis of cold tolerance in wheat
- (2020) Yong Zhao et al. MOLECULAR BREEDING
- SpikeSegNet-a deep learning approach utilizing encoder-decoder network with hourglass for spike segmentation and counting in wheat plant from visual imaging
- (2020) Tanuj Misra et al. Plant Methods
- Scalable learning for bridging the species gap in image-based plant phenotyping
- (2020) Daniel Ward et al. COMPUTER VISION AND IMAGE UNDERSTANDING
- Root anatomy based on root cross-section image analysis with deep learning
- (2020) Chaoxin Wang et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- A review of computer vision technologies for plant phenotyping
- (2020) Zhenbo Li et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Multi-class fruit-on-plant detection for apple in SNAP system using Faster R-CNN
- (2020) Fangfang Gao et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Sorghum Panicle Detection and Counting Using Unmanned Aerial System Images and Deep Learning
- (2020) Zhe Lin et al. Frontiers in Plant Science
- A Comprehensive Survey on Transfer Learning
- (2020) Fuzhen Zhuang et al. PROCEEDINGS OF THE IEEE
- A Mobile-Based Deep Learning Model for Cassava Disease Diagnosis
- (2019) Amanda Ramcharan et al. Frontiers in Plant Science
- UAV-Based High Throughput Phenotyping in Citrus Utilizing Multispectral Imaging and Artificial Intelligence
- (2019) Yiannis Ampatzidis et al. Remote Sensing
- Deep learning for real-time fruit detection and orchard fruit load estimation: benchmarking of ‘MangoYOLO’
- (2019) A. Koirala et al. PRECISION AGRICULTURE
- Development and evaluation of a low-cost and smart technology for precision weed management utilizing artificial intelligence
- (2019) Victor Partel et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Crop Yield Prediction Using Deep Neural Networks
- (2019) Saeed Khaki et al. Frontiers in Plant Science
- Leveraging Image Analysis for High-Throughput Plant Phenotyping
- (2019) Sruti Das Choudhury et al. Frontiers in Plant Science
- Single-Shot Convolution Neural Networks for Real-Time Fruit Detection Within the Tree
- (2019) Kushtrim Bresilla et al. Frontiers in Plant Science
- DeepCount: In-Field Automatic Quantification of Wheat Spikes Using Simple Linear Iterative Clustering and Deep Convolutional Neural Networks
- (2019) Pouria Sadeghi-Tehran et al. Frontiers in Plant Science
- Unmanned aerial system and satellite-based high resolution imagery for high-throughput phenotyping in dry bean
- (2019) Sindhuja Sankaran et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- A Deep Learning-Based Approach for High-Throughput Hypocotyl Phenotyping
- (2019) Orsolya Dobos et al. PLANT PHYSIOLOGY
- RootNav 2.0: Deep learning for automatic navigation of complex plant root architectures
- (2019) Robail Yasrab et al. GigaScience
- Estimating Canopy Parameters Based on the Stem Position in Apple Trees Using a 2D LiDAR
- (2019) Nikos Tsoulias et al. Agronomy-Basel
- Hyperspectral imaging combined with machine learning as a tool to obtain high‐throughput plant salt‐stress phenotyping
- (2019) Xuping Feng et al. PLANT JOURNAL
- Classification of sour lemons based on apparent defects using stochastic pooling mechanism in deep convolutional neural networks
- (2019) Ahmad Jahanbakhshi et al. SCIENTIA HORTICULTURAE
- Seed-per-pod estimation for plant breeding using deep learning
- (2018) L.C. Uzal et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Deep learning in agriculture: A survey
- (2018) Andreas Kamilaris et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Deep learning models for plant disease detection and diagnosis
- (2018) Konstantinos P. Ferentinos COMPUTERS AND ELECTRONICS IN AGRICULTURE
- An explainable deep machine vision framework for plant stress phenotyping
- (2018) Sambuddha Ghosal et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- Application of Deep Learning Architectures for Accurate and Rapid Detection of Internal Mechanical Damage of Blueberry Using Hyperspectral Transmittance Data
- (2018) et al. SENSORS
- Translating High-Throughput Phenotyping into Genetic Gain
- (2018) José Luis Araus et al. TRENDS IN PLANT SCIENCE
- Genomic Prediction in a Multiploid Crop: Genotype by Environment Interaction and Allele Dosage Effects on Predictive Ability in Banana
- (2018) Moses Nyine et al. Plant Genome
- Deep Learning: Individual Maize Segmentation From Terrestrial Lidar Data Using Faster R-CNN and Regional Growth Algorithms
- (2018) Shichao Jin et al. Frontiers in Plant Science
- Deep Learning for Computer Vision: A Brief Review
- (2018) Athanasios Voulodimos et al. Computational Intelligence and Neuroscience
- Erratum to: Deep machine learning provides state-of-the-art performance in image-based plant phenotyping
- (2018) Michael P Pound et al. GigaScience
- Deep phenotyping: deep learning for temporal phenotype/genotype classification
- (2018) Sarah Taghavi Namin et al. Plant Methods
- Machine Learning in Agriculture: A Review
- (2018) Konstantinos Liakos et al. SENSORS
- Deep Learning for Plant Stress Phenotyping: Trends and Future Perspectives
- (2018) Asheesh Kumar Singh et al. TRENDS IN PLANT SCIENCE
- Branch detection for apple trees trained in fruiting wall architecture using depth features and Regions-Convolutional Neural Network (R-CNN)
- (2018) Jing Zhang et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Detection and analysis of wheat spikes using Convolutional Neural Networks
- (2018) Md Mehedi Hasan et al. Plant Methods
- Hyperspectral Image Superresolution by Transfer Learning
- (2017) Yuan Yuan et al. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
- Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
- (2017) Shaoqing Ren et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Hyperspectral image super-resolution using deep convolutional neural network
- (2017) Yunsong Li et al. NEUROCOMPUTING
- A survey of deep neural network architectures and their applications
- (2017) Weibo Liu et al. NEUROCOMPUTING
- Automated Identification of Northern Leaf Blight-Infected Maize Plants from Field Imagery Using Deep Learning
- (2017) Chad DeChant et al. PHYTOPATHOLOGY
- Super-Resolution of Plant Disease Images for the Acceleration of Image-based Phenotyping and Vigor Diagnosis in Agriculture
- (2017) Kyosuke Yamamoto et al. SENSORS
- Digital Counts of Maize Plants by Unmanned Aerial Vehicles (UAVs)
- (2017) Friederike Gnädinger et al. Remote Sensing
- Deep Plant Phenomics: A Deep Learning Platform for Complex Plant Phenotyping Tasks
- (2017) Jordan R. Ubbens et al. Frontiers in Plant Science
- Deep machine learning provides state-of-the-art performance in image-based plant phenotyping
- (2017) Michael P. Pound et al. GigaScience
- Finely-grained annotated datasets for image-based plant phenotyping
- (2016) Massimo Minervini et al. PATTERN RECOGNITION LETTERS
- High-Throughput Phenotyping of Maize Leaf Physiological and Biochemical Traits Using Hyperspectral Reflectance
- (2016) Craig R. Yendrek et al. PLANT PHYSIOLOGY
- Image Based Mango Fruit Detection, Localisation and Yield Estimation Using Multiple View Geometry
- (2016) Madeleine Stein et al. SENSORS
- DeepFruits: A Fruit Detection System Using Deep Neural Networks
- (2016) Inkyu Sa et al. SENSORS
- Using Deep Learning for Image-Based Plant Disease Detection
- (2016) Sharada P. Mohanty et al. Frontiers in Plant Science
- Deep Neural Networks Based Recognition of Plant Diseases by Leaf Image Classification
- (2016) Srdjan Sladojevic et al. Computational Intelligence and Neuroscience
- Towards Real-Time Object Detection on Embedded Systems
- (2016) Huizi Mao et al. IEEE Transactions on Emerging Topics in Computing
- Lights, camera, action: high-throughput plant phenotyping is ready for a close-up
- (2015) Noah Fahlgren et al. CURRENT OPINION IN PLANT BIOLOGY
- Image Analysis: The New Bottleneck in Plant Phenotyping [Applications Corner]
- (2015) Massimo Minervini et al. IEEE SIGNAL PROCESSING MAGAZINE
- Deep learning
- (2015) Yann LeCun et al. NATURE
- Deep learning in neural networks: An overview
- (2015) Jürgen Schmidhuber NEURAL NETWORKS
- A Novel Image-Analysis Toolbox Enabling Quantitative Analysis of Root System Architecture
- (2011) Guillaume Lobet et al. PLANT PHYSIOLOGY
- A Survey on Transfer Learning
- (2009) Sinno Jialin Pan et al. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreFind the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
Search