FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4205339373> ?p ?o ?g. }

• W4205339373 abstract "Robust and automated segmentation of leaves and other backgrounds is a core prerequisite of most approaches in high-throughput field phenotyping. So far, the possibilities of deep learning approaches for this purpose have not been explored adequately, partly due to a lack of publicly available, appropriate datasets. This study presents a workflow based on DeepLab v3+ and on a diverse annotated dataset of 190 RGB (350 x 350 pixels) images. Images of winter wheat plants of 76 different genotypes and developmental stages have been acquired throughout multiple years at high resolution in outdoor conditions using nadir view, encompassing a wide range of imaging conditions. Inconsistencies of human annotators in complex images have been quantified, and metadata information of camera settings has been included. The proposed approach achieves an intersection over union (IoU) of 0.77 and 0.90 for plants and soil, respectively. This outperforms the benchmarked machine learning methods which use Support Vector Classifier and/or Random Forrest. The results show that a small but carefully chosen and annotated set of images can provide a good basis for a powerful segmentation pipeline. Compared to earlier methods based on machine learning, the proposed method achieves better performance on the selected dataset in spite of using a deep learning approach with limited data. Increasing the amount of publicly available data with high human agreement on annotations and further development of deep neural network architectures will provide high potential for robust field-based plant segmentation in the near future. This, in turn, will be a cornerstone of data-driven improvement in crop breeding and agricultural practices of global benefit." @default.
• W4205339373 created "2022-01-26" @default.
• W4205339373 creator A5000845966 @default.
• W4205339373 creator A5001254143 @default.
• W4205339373 creator A5004761344 @default.
• W4205339373 creator A5018489763 @default.
• W4205339373 creator A5036247785 @default.
• W4205339373 creator A5041969138 @default.
• W4205339373 creator A5052236177 @default.
• W4205339373 creator A5054933728 @default.
• W4205339373 date "2022-01-04" @default.
• W4205339373 modified "2023-10-10" @default.
• W4205339373 title "Outdoor Plant Segmentation With Deep Learning for High-Throughput Field Phenotyping on a Diverse Wheat Dataset" @default.
• W4205339373 cites W1967395374 @default.
• W4205339373 cites W1969784023 @default.
• W4205339373 cites W2034794296 @default.
• W4205339373 cites W2044651338 @default.
• W4205339373 cites W2067877300 @default.
• W4205339373 cites W2069209512 @default.
• W4205339373 cites W2080178568 @default.
• W4205339373 cites W2108358988 @default.
• W4205339373 cites W2145675077 @default.
• W4205339373 cites W2161558103 @default.
• W4205339373 cites W2243003515 @default.
• W4205339373 cites W2271798434 @default.
• W4205339373 cites W2516646655 @default.
• W4205339373 cites W2518417964 @default.
• W4205339373 cites W2518904328 @default.
• W4205339373 cites W2523168882 @default.
• W4205339373 cites W2548258044 @default.
• W4205339373 cites W2586871584 @default.
• W4205339373 cites W2601082556 @default.
• W4205339373 cites W2616262716 @default.
• W4205339373 cites W2618530766 @default.
• W4205339373 cites W2739413041 @default.
• W4205339373 cites W2769625730 @default.
• W4205339373 cites W2790979755 @default.
• W4205339373 cites W2802213910 @default.
• W4205339373 cites W2843415492 @default.
• W4205339373 cites W2890385962 @default.
• W4205339373 cites W2902694634 @default.
• W4205339373 cites W2911964244 @default.
• W4205339373 cites W2940692219 @default.
• W4205339373 cites W2945925278 @default.
• W4205339373 cites W2960049883 @default.
• W4205339373 cites W2962782553 @default.
• W4205339373 cites W2979936711 @default.
• W4205339373 cites W2985835333 @default.
• W4205339373 cites W2987252287 @default.
• W4205339373 cites W3007017931 @default.
• W4205339373 cites W3014641072 @default.
• W4205339373 cites W3036882155 @default.
• W4205339373 cites W3064678530 @default.
• W4205339373 cites W3084392573 @default.
• W4205339373 cites W4233070360 @default.
• W4205339373 doi "https://doi.org/10.3389/fpls.2021.774068" @default.
• W4205339373 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35058948" @default.
• W4205339373 hasPublicationYear "2022" @default.
• W4205339373 type Work @default.
• W4205339373 citedByCount "16" @default.
• W4205339373 countsByYear W42053393732022 @default.
• W4205339373 countsByYear W42053393732023 @default.
• W4205339373 crossrefType "journal-article" @default.
• W4205339373 hasAuthorship W4205339373A5000845966 @default.
• W4205339373 hasAuthorship W4205339373A5001254143 @default.
• W4205339373 hasAuthorship W4205339373A5004761344 @default.
• W4205339373 hasAuthorship W4205339373A5018489763 @default.
• W4205339373 hasAuthorship W4205339373A5036247785 @default.
• W4205339373 hasAuthorship W4205339373A5041969138 @default.
• W4205339373 hasAuthorship W4205339373A5052236177 @default.
• W4205339373 hasAuthorship W4205339373A5054933728 @default.
• W4205339373 hasBestOaLocation W42053393731 @default.
• W4205339373 hasConcept C108583219 @default.
• W4205339373 hasConcept C111919701 @default.
• W4205339373 hasConcept C119857082 @default.
• W4205339373 hasConcept C153180895 @default.
• W4205339373 hasConcept C154945302 @default.
• W4205339373 hasConcept C177212765 @default.
• W4205339373 hasConcept C202444582 @default.
• W4205339373 hasConcept C33923547 @default.
• W4205339373 hasConcept C41008148 @default.
• W4205339373 hasConcept C50644808 @default.
• W4205339373 hasConcept C77088390 @default.
• W4205339373 hasConcept C82990744 @default.
• W4205339373 hasConcept C89600930 @default.
• W4205339373 hasConcept C93518851 @default.
• W4205339373 hasConcept C95623464 @default.
• W4205339373 hasConcept C9652623 @default.
• W4205339373 hasConcept C97931131 @default.
• W4205339373 hasConceptScore W4205339373C108583219 @default.
• W4205339373 hasConceptScore W4205339373C111919701 @default.
• W4205339373 hasConceptScore W4205339373C119857082 @default.
• W4205339373 hasConceptScore W4205339373C153180895 @default.
• W4205339373 hasConceptScore W4205339373C154945302 @default.
• W4205339373 hasConceptScore W4205339373C177212765 @default.
• W4205339373 hasConceptScore W4205339373C202444582 @default.
• W4205339373 hasConceptScore W4205339373C33923547 @default.
• W4205339373 hasConceptScore W4205339373C41008148 @default.
• W4205339373 hasConceptScore W4205339373C50644808 @default.
• W4205339373 hasConceptScore W4205339373C77088390 @default.

• next