Browse State-of-the-Art › Plant Phenotyping
Plant Phenotyping
29 papers with code · 0 benchmarks · 3 datasets archive 2025-07-28
Plant Phenotyping refers to the use of various techniques and methods to measure and describe the external characteristics and traits of plants. In the field of machine learning, Plant Phenotyping typically involves the use of tools such as image processing, computer vision, sensor technologies, etc., to automatically capture and analyze data related to the morphology, structure, and growth patterns of plants.
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
No benchmark for this task in the archive.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
3 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
No subtask under this task in the archive's task tree.
Parent tasks archive 2025-07-28
Most implemented papers archive 2025-07-28
29 shown of 29 papers with code (74 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
-
30 Mar 2020 4 repositories listedHigh-resolution cameras have become very helpful for plant phenotyping by providing a mechanism for tasks such as target versus background discrimination, and the measurement and analysis of fine-above-ground plant…
-
24 Mar 2020 3 repositories listedThis study is applicable to use of synthetic data for automating the measurement of phenotypic traits.
-
10 Apr 2023 2 repositories listedTherefore, we present CherryPicker, an automatic pipeline that reconstructs photo-metric point clouds of trees, performs semantic segmentation and extracts their topological structure in form of a skeleton.
-
6 Jan 2023 2 repositories listedPrecision Agriculture and especially the application of automated weed intervention represents an increasingly essential research area, as sustainability and efficiency considerations are becoming more and more relevant.
-
2 Sep 2020 2 repositories listedSupervised learning is often used to count objects in images, but for counting small, densely located objects, the required image annotations are burdensome to collect.
-
30 Apr 2019 2 repositories listedThe use of this protocol for two-dimensional plant phenotyping will allow data capture from different cameras and environments, with comparison on the same physical scale.
-
30 Apr 2025 1 repository listedThrough this review, we aim to provide insights into how these diverse 3D reconstruction techniques can be effectively leveraged for automated and high-throughput plant phenotyping, contributing to the next generation…
-
28 Apr 2025 1 repository listedPlant phenotyping increasingly relies on (semi-)automated image-based analysis workflows to improve its accuracy and scalability.
-
9 Mar 2025 1 repository listedWe present the Growth Modelling (GroMo) challenge, which is designed for two primary tasks: (1) plant age prediction and (2) leaf count estimation, both essential for crop monitoring and precision agriculture.
-
31 Jul 2024 1 repository listedThe proposed STN-YOLO aims to enhance the model's effectiveness by focusing on important areas of the image and improving the spatial invariance of the model before the detection process.
-
3 Jul 2024 1 repository listedBy leveraging depth data, our method mitigates parallax effects and thus facilitates more accurate pixel alignment across camera modalities.
-
6 Dec 2023 1 repository listedA prerequisite for realistic and sharp crop image generation is the integration of multiple growth-influencing conditions in a model, such as an image of an initial growth stage, the associated growth time, and further…
-
23 Jun 2023 1 repository listedRegarding the robust tracking of vegetable plants, to solve the challenging problem of associating vegetables with similar color and texture in consecutive images, in this paper, a novel method of Multiple Object…
-
24 May 2023 1 repository listedIn addition, a systematic review of various agricultural applications exploiting these label-efficient algorithms, such as precision agriculture, plant phenotyping, and postharvest quality assessment, is presented.
-
16 May 2023 1 repository listedLeaf Only SAM does not perform better than the fine-tuned Mask R-CNN model on our data, but the SAM based model does not require any extra training or annotation of our new dataset.
-
1 Mar 2023 1 repository listedWe studied the effects of the domain of the pretraining (source) dataset on the downstream performance and the influence of redundancy in the pretraining dataset on the quality of learned representations.
-
24 Jan 2023 1 repository listedIn this way, the current work is designed to provide the plant phenotyping community with (i) methods for fast and accurate image-based feature extraction that require minimal training data, and (ii) a new…
-
14 Oct 2022 1 repository listedIn this paper, we address the problem of joint semantic, plant instance, and leaf instance segmentation of crop fields from RGB data.
-
10 Apr 2022 1 repository listedIn agricultural image analysis, optimal model performance is keenly pursued for better fulfilling visual recognition tasks (e.
-
29 Mar 2022 1 repository listedAs an essential prerequisite task in image-based plant phenotyping, leaf segmentation has garnered increasing attention in recent years.
-
8 Aug 2021 1 repository listedIn this work, we present the LeafMask neural network, a new end-to-end model to delineate each leaf region and count the number of leaves, with two main components: 1) the mask assembly module merging position-sensitive…
-
22 Jul 2021 1 repository listedIn order to apply the recent successes of machine learning and automated plant phenotyping on a large scale using agricultural robotics, efficient and general algorithms must be designed to intelligently split crop…
-
14 Jun 2021 1 repository listedTo deal with this problem, in this paper, we propose an object-guided instance segmentation method.
-
7 Jun 2020 1 repository listedTo overcome this challenge, active learning algorithms have been proposed that reduce the amount of labeling needed by deep learning models to achieve good predictive performance.
-
15 Jan 2020 1 repository listed Syntology ran 1 of 3 samples · 2 unverified · 3 pointer-only (licence)Deep neural networks have shown excellent performances in many real-world applications.
-
30 Oct 2019 1 repository listedWe also present a toolchain that can be used to create phenotyping farms for use in Gazebo simulations.
-
21 Jan 2019 1 repository listedA looming question that must be solved before robotic plant phenotyping capabilities can have significant impact to crop improvement programs is scalability.
-
26 Jul 2018 1 repository listedWe propose a new and, arguably, a very simple reduction of instance segmentation to semantic segmentation.
-
24 Aug 2017 1 repository listedIn this paper, we investigate the problem of counting rosette leaves from an RGB image, an important task in plant phenotyping.
Syntology lines on 1 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections