Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data | Paper Citation Record

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This paper cites Tomato (solanum lycopersicum): A model fruit-bearing crop.

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Tomato (solanum lycopersicum): A model fruit-bearing crop

Reference 1

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This paper cites Cobb, Genevieve DeClerck, Anthony Greenberg, Randy Clark, and Susan McCouch.

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Cobb, Genevieve DeClerck, Anthony Greenberg, Randy Clark, and Susan McCouch

Reference 2

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This paper cites Quantitative extraction and evaluation of tomato fruit phenotypes based on image recognition.

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Quantitative extraction and evaluation of tomato fruit phenotypes based on image recognition

Reference 4

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This paper cites Tomato multi-angle multi-pose dataset for fine-grained phenotyping.

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Tomato multi-angle multi-pose dataset for fine-grained phenotyping

Reference 5

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Unresolved cited work

Reference 6

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This paper cites 3dphenomvs: A low-cost 3d tomato phenotyping pipeline using 3d reconstruction point cloud based on multiview images.

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data 3dphenomvs: A low-cost 3d tomato phenotyping pipeline using 3d reconstruction point cloud based on multiview images

Reference 7

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Observation 2df989f7-8195-4ed5-bf57-b3e8bde83180 · outbound

This paper cites White, J.

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data White, J

Reference 9

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This paper cites Michels, Soren Pirk, Chia-Chun Fu, and Wojciech Palubicki.

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Michels, Soren Pirk, Chia-Chun Fu, and Wojciech Palubicki

Reference 10

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Unresolved cited work

Reference 11

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This paper cites Effectiveness of training with procedurally generated synthetic images of crop plants.

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Effectiveness of training with procedurally generated synthetic images of crop plants

Reference 12

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This paper cites Winsyn: A high resolution testbed for synthetic data.

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Winsyn: A high resolution testbed for synthetic data

Reference 13

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This paper cites Bhattacharyya.

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Bhattacharyya

Reference 14

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Observation 10f14b9a-3df7-42cf-a9c0-6650980766b0 · outbound

This paper cites Sam 3: Segment anything with concepts, 2025.

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Sam 3: Segment anything with concepts, 2025

Reference 15

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This paper cites Segment anything is not always perfect: An investigation of sam on different real-world applications.

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Segment anything is not always perfect: An investigation of sam on different real-world applications

Reference 16

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correction dated 2024-09-12. Source: crossref record 10.1007/s11633-024-1526-0->10.1007/s11633-023-1385-0:correction, observed 2026-07-11T03:08:16.498698+00:00. This notice travels one citation hop only.

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This paper cites Tsaftaris.

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Tsaftaris

Reference 18

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This paper cites Evaluating the efficacy of segment anything model for delineating agriculture and urban green spaces in multiresolution aerial and spaceborne remote sensing images.

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Evaluating the efficacy of segment anything model for delineating agriculture and urban green spaces in multiresolution aerial and spaceborne remote sensing images

Reference 19

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This paper cites Agri-fm+: A self-supervised foundation model for agricultural vision.

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Agri-fm+: A self-supervised foundation model for agricultural vision

Reference 20

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This paper cites Few-shot adaptation of grounding dino for agricultural domain.

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Few-shot adaptation of grounding dino for agricultural domain

Reference 21

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This paper cites Bailey, and J.

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Bailey, and J

Reference 22

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Unresolved cited work

Reference 23

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This paper cites The use of plant models in deep learning: an application to leaf counting in rosette plants.

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data The use of plant models in deep learning: an application to leaf counting in rosette plants

Reference 25

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Unresolved cited work

Reference 26

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This paper cites Schwing, Robert Brunner, Hrant Khachatrian, Hovnatan Karapetyan, Ivan Dozier, Greg Rose, David Wilson, Adrian Tudor, Naira Hovakimyan, Thomas S.

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Schwing, Robert Brunner, Hrant Khachatrian, Hovnatan Karapetyan, Ivan Dozier, Greg Rose, David Wilson, Adrian Tudor, Naira Hovakimyan, Thomas S

Reference 27

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This paper cites Konovalov, Bronson Philippa, Peter Ridd, Jake C.

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Konovalov, Bronson Philippa, Peter Ridd, Jake C

Reference 28

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This paper cites A realistic synthetic mushroom scenes dataset.

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data A realistic synthetic mushroom scenes dataset

Reference 29

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This paper cites Cropdeep: The crop vision dataset for deep-learning-based classification and detection in precision agriculture.

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Cropdeep: The crop vision dataset for deep-learning-based classification and detection in precision agriculture

Reference 30

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This paper cites Deep convolutional neural networks for image-based convolvulus sepium detection in sugar beet fields.

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Deep convolutional neural networks for image-based convolvulus sepium detection in sugar beet fields

Reference 31

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This paper cites Domain generalization for crop segmentation with standardized ensemble knowledge distillation.

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Domain generalization for crop segmentation with standardized ensemble knowledge distillation

Reference 32

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This paper cites Plantdreamer: Achieving realistic 3d plant models with diffusion-guided gaussian splatting.

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Plantdreamer: Achieving realistic 3d plant models with diffusion-guided gaussian splatting

Reference 34

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This paper cites Sapkota, Sorin Popescu, Nithya Rajan, Ramon G.

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Sapkota, Sorin Popescu, Nithya Rajan, Ramon G

Reference 36

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Synthset: Generative diffusion model for semantic segmentation in precision agriculture

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This paper cites Beyond annotations: Efficient wheat head segmentation using l-systems, game engines, and student-teacher models.

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Beyond annotations: Efficient wheat head segmentation using l-systems, game engines, and student-teacher models

Reference 38

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Efficient wheat head segmentation with minimal annotation: A generative approach

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data A dataset for semantic and instance segmentation of modern fruit orchards

Reference 43

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This paper cites De Visser, Gerie van der Heijden, and Gerhard Buck-Sorlin.

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data De Visser, Gerie van der Heijden, and Gerhard Buck-Sorlin

Reference 46

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This paper cites A functional–structural plant model for dwarf tomato ideotype identification in vertical farming.

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data A functional–structural plant model for dwarf tomato ideotype identification in vertical farming

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Unresolved cited work

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This paper cites LaboroTomato : Instance segmentation dataset.

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data LaboroTomato : Instance segmentation dataset

Reference 51

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Tomato fruit detection and counting in greenhouses using deep learning

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Tsironis, S

Reference 53

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This paper cites Benchmark of deep learning and a proposed hsv colour space models for the detection and classification of greenhouse tomato.

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Benchmark of deep learning and a proposed hsv colour space models for the detection and classification of greenhouse tomato

Reference 54

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data The Algorithmic Beauty of Plants

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data M e ch and P

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Unresolved cited work

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Torres Quezada

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This paper cites Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen.

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Robust fine-tuning of zero-shot models

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Encoder-decoder with atrous separable convolution for semantic image segmentation

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Segformer: Simple and efficient design for semantic segmentation with transformers

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Your ViT is Secretly an Image Segmentation Model

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Zero-shot hierarchical plant segmentation via foundation segmentation models and text-to-image attention

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data An opinion on imaging challenges in phenotyping field crops

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This paper cites Recognition and localization methods for vision-based fruit picking robots: A review.

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Recognition and localization methods for vision-based fruit picking robots: A review

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This paper cites Quantifying the importance of a realistic tomato (solanum lycopersicum) leaflet shape for 3-d light modelling.

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Quantifying the importance of a realistic tomato (solanum lycopersicum) leaflet shape for 3-d light modelling

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This paper cites Development of a tomato functional–structural plant model for digital twin applications.

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Development of a tomato functional–structural plant model for digital twin applications

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This paper cites Xfrog - procedural organic 3d modeler [3d models].

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Xfrog - procedural organic 3d modeler [3d models]

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Prusinkiewicz, R

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data The use of positional information in the modeling of plants

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Mohanty, David P

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data COSYS-AIRSIM : A real-time simulation framework expanded for complex industrial applications

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data in silico Plants , volume =

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data and Pirk, Soren and Fu, Chia-Chun and Palubicki, Wojciech , title =

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Graph-Grammars and Their Application to Computer Science , pages =

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data and Lindenmayer, A

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data The Algorithmic Beauty of Plants , publisher =

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data and Mjolsness, Eric , title =

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data The Use of Positional Information in the Modeling of Plants , booktitle =

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Unresolved cited work

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data , title =

Reference 86

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Prusinkiewicz and R

Reference 87

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Mercer, P

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Frontiers in Plant Science , author =

Reference 89

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Annual Modeling and Simulation Conference (ANNSIM) , pages =

Reference 90

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data and de Visser, P

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Annals of Botany , volume =

Reference 92

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data 2020 , issn =

Reference 93

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data in silico Plants , volume =

Reference 94

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data in silico Plants , volume =

Reference 95

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data and van der Heijden, Gerie and Buck-Sorlin, Gerhard , title =

Reference 96

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data 2024 , eprint =

Reference 97

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data A Physically-inspired Approach to the Simulation of Plant Wilting , year =

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Agronomy , volume =

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data , title =

Reference 100

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data in silico Plants , volume =

Reference 101

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops , month =

Reference 102

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data 1999 , publisher =

Reference 103

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Journal of Experimental Botany , volume =

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data and Bourou, S

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data 2020 , howpublished =

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Sci Data , month =

Reference 107

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data 2025 , doi =

Reference 108

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data and DeClerck, Genevieve and Greenberg, Anthony and Clark, Randy and McCouch, Susan , title =

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data 2008 , doi =

Reference 110

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Frontiers in Plant Science , volume =

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Horticulture Research , volume =

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data Unresolved cited work

Reference 113

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data 2025 , eprint =

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data and Thomasson, J

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Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data International Conference on Learning Representations (ICLR) , year =

Reference 116

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