153 related articles for article (PubMed ID: 31850020)
1. Convolutional Neural Net-Based Cassava Storage Root Counting Using Real and Synthetic Images.
Atanbori J; Montoya-P ME; Selvaraj MG; French AP; Pridmore TP
Front Plant Sci; 2019; 10():1516. PubMed ID: 31850020
[TBL] [Abstract][Full Text] [Related]
2. Super resolution for root imaging.
Ruiz-Munoz JF; Nimmagadda JK; Dowd TG; Baciak JE; Zare A
Appl Plant Sci; 2020 Jul; 8(7):e11374. PubMed ID: 32765973
[TBL] [Abstract][Full Text] [Related]
3. A low-cost aeroponic phenotyping system for storage root development: unravelling the below-ground secrets of cassava (
Selvaraj MG; Montoya-P ME; Atanbori J; French AP; Pridmore T
Plant Methods; 2019; 15():131. PubMed ID: 31728153
[TBL] [Abstract][Full Text] [Related]
4. Enhancing classification of cells procured from bone marrow aspirate smears using generative adversarial networks and sequential convolutional neural network.
Hazra D; Byun YC; Kim WJ
Comput Methods Programs Biomed; 2022 Sep; 224():107019. PubMed ID: 35878483
[TBL] [Abstract][Full Text] [Related]
5. Image generation by GAN and style transfer for agar plate image segmentation.
Andreini P; Bonechi S; Bianchini M; Mecocci A; Scarselli F
Comput Methods Programs Biomed; 2020 Feb; 184():105268. PubMed ID: 31891902
[TBL] [Abstract][Full Text] [Related]
6. Use of synthetic images for training a deep learning model for weed detection and biomass estimation in cotton.
Sapkota BB; Popescu S; Rajan N; Leon RG; Reberg-Horton C; Mirsky S; Bagavathiannan MV
Sci Rep; 2022 Nov; 12(1):19580. PubMed ID: 36379963
[TBL] [Abstract][Full Text] [Related]
7. Conditional generative adversarial network for 3D rigid-body motion correction in MRI.
Johnson PM; Drangova M
Magn Reson Med; 2019 Sep; 82(3):901-910. PubMed ID: 31006909
[TBL] [Abstract][Full Text] [Related]
8. Breast cancer detection using synthetic mammograms from generative adversarial networks in convolutional neural networks.
Guan S; Loew M
J Med Imaging (Bellingham); 2019 Jul; 6(3):031411. PubMed ID: 30915386
[TBL] [Abstract][Full Text] [Related]
9. Data-driven crop growth simulation on time-varying generated images using multi-conditional generative adversarial networks.
Drees L; Demie DT; Paul MR; Leonhardt J; Seidel SJ; Döring TF; Roscher R
Plant Methods; 2024 Jun; 20(1):93. PubMed ID: 38879522
[TBL] [Abstract][Full Text] [Related]
10. High-content image generation for drug discovery using generative adversarial networks.
Hussain S; Anees A; Das A; Nguyen BP; Marzuki M; Lin S; Wright G; Singhal A
Neural Netw; 2020 Dec; 132():353-363. PubMed ID: 32977280
[TBL] [Abstract][Full Text] [Related]
11. Identification and expression analyses of new potential regulators of xylem development and cambium activity in cassava (Manihot esculenta).
Siebers T; Catarino B; Agusti J
Planta; 2017 Mar; 245(3):539-548. PubMed ID: 27900471
[TBL] [Abstract][Full Text] [Related]
12. SynthEye: Investigating the Impact of Synthetic Data on Artificial Intelligence-assisted Gene Diagnosis of Inherited Retinal Disease.
Veturi YA; Woof W; Lazebnik T; Moghul I; Woodward-Court P; Wagner SK; Cabral de Guimarães TA; Daich Varela M; Liefers B; Patel PJ; Beck S; Webster AR; Mahroo O; Keane PA; Michaelides M; Balaskas K; Pontikos N
Ophthalmol Sci; 2023 Jun; 3(2):100258. PubMed ID: 36685715
[TBL] [Abstract][Full Text] [Related]
13. RootNav 2.0: Deep learning for automatic navigation of complex plant root architectures.
Yasrab R; Atkinson JA; Wells DM; French AP; Pridmore TP; Pound MP
Gigascience; 2019 Nov; 8(11):. PubMed ID: 31702012
[TBL] [Abstract][Full Text] [Related]
14. Inside out: transforming images of lab-grown plants for machine learning applications in agriculture.
Krosney AE; Sotoodeh P; Henry CJ; Beck MA; Bidinosti CP
Front Artif Intell; 2023; 6():1200977. PubMed ID: 37483870
[TBL] [Abstract][Full Text] [Related]
15. Development and qualification of a machine learning algorithm for automated hair counting.
Sacha JP; Caterino TL; Fisher BK; Carr GJ; Youngquist RS; D'Alessandro BM; Melione A; Canfield D; Bergfeld WF; Piliang MP; Kainkaryam R; Davis MG
Int J Cosmet Sci; 2021 Nov; 43 Suppl 1():S34-S41. PubMed ID: 34426987
[TBL] [Abstract][Full Text] [Related]
16. Improved automatic detection of herpesvirus secondary envelopment stages in electron microscopy by augmenting training data with synthetic labelled images generated by a generative adversarial network.
Shaga Devan K; Walther P; von Einem J; Ropinski T; A Kestler H; Read C
Cell Microbiol; 2021 Feb; 23(2):e13280. PubMed ID: 33073426
[TBL] [Abstract][Full Text] [Related]
17. A material decomposition method for dual-energy CT via dual interactive Wasserstein generative adversarial networks.
Shi Z; Li H; Cao Q; Wang Z; Cheng M
Med Phys; 2021 Jun; 48(6):2891-2905. PubMed ID: 33704786
[TBL] [Abstract][Full Text] [Related]
18. Assessing the Storage Root Development of Cassava with a New Analysis Tool.
Wilhelm J; Wojciechowski T; Postma JA; Jollet D; Heinz K; Böckem V; Müller-Linow M
Plant Phenomics; 2022; 2022():9767820. PubMed ID: 37228350
[TBL] [Abstract][Full Text] [Related]
19. AI Radar Sensor: Creating Radar Depth Sounder Images Based on Generative Adversarial Network.
Rahnemoonfar M; Johnson J; Paden J
Sensors (Basel); 2019 Dec; 19(24):. PubMed ID: 31842359
[TBL] [Abstract][Full Text] [Related]
20. Generative adversarial network based synthetic data training model for lightweight convolutional neural networks.
Rather IH; Kumar S
Multimed Tools Appl; 2023 May; ():1-23. PubMed ID: 37362646
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]