423 related articles for article (PubMed ID: 36399435)
1. A deep learning generative model approach for image synthesis of plant leaves.
Benfenati A; Bolzi D; Causin P; Oberti R
PLoS One; 2022; 17(11):e0276972. PubMed ID: 36399435
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. 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]
4. 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]
5. Automatic generation of artificial images of leukocytes and leukemic cells using generative adversarial networks (syntheticcellgan).
Barrera K; Merino A; Molina A; Rodellar J
Comput Methods Programs Biomed; 2023 Feb; 229():107314. PubMed ID: 36565666
[TBL] [Abstract][Full Text] [Related]
6. SpeckleGAN: a generative adversarial network with an adaptive speckle layer to augment limited training data for ultrasound image processing.
Bargsten L; Schlaefer A
Int J Comput Assist Radiol Surg; 2020 Sep; 15(9):1427-1436. PubMed ID: 32556953
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. pix2xray: converting RGB images into X-rays using generative adversarial networks.
Haiderbhai M; Ledesma S; Lee SC; Seibold M; Fürnstahl P; Navab N; Fallavollita P
Int J Comput Assist Radiol Surg; 2020 Jun; 15(6):973-980. PubMed ID: 32342258
[TBL] [Abstract][Full Text] [Related]
9. Deep Neural Networks Based Recognition of Plant Diseases by Leaf Image Classification.
Sladojevic S; Arsenovic M; Anderla A; Culibrk D; Stefanovic D
Comput Intell Neurosci; 2016; 2016():3289801. PubMed ID: 27418923
[TBL] [Abstract][Full Text] [Related]
10. Multimodal Hybrid Deep Learning Approach to Detect Tomato Leaf Disease Using Attention Based Dilated Convolution Feature Extractor with Logistic Regression Classification.
Islam MS; Sultana S; Farid FA; Islam MN; Rashid M; Bari BS; Hashim N; Husen MN
Sensors (Basel); 2022 Aug; 22(16):. PubMed ID: 36015839
[TBL] [Abstract][Full Text] [Related]
11. 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]
12. Assessment of Generative Adversarial Networks Model for Synthetic Optical Coherence Tomography Images of Retinal Disorders.
Zheng C; Xie X; Zhou K; Chen B; Chen J; Ye H; Li W; Qiao T; Gao S; Yang J; Liu J
Transl Vis Sci Technol; 2020 May; 9(2):29. PubMed ID: 32832202
[TBL] [Abstract][Full Text] [Related]
13. Assessment of Deep Generative Models for High-Resolution Synthetic Retinal Image Generation of Age-Related Macular Degeneration.
Burlina PM; Joshi N; Pacheco KD; Liu TYA; Bressler NM
JAMA Ophthalmol; 2019 Mar; 137(3):258-264. PubMed ID: 30629091
[TBL] [Abstract][Full Text] [Related]
14. Synthetic Generation of 3D Microscopy Images using Generative Adversarial Networks.
Narotamo H; Ouarne M; Franco CA; Silveira M
Annu Int Conf IEEE Eng Med Biol Soc; 2022 Jul; 2022():549-552. PubMed ID: 36086569
[TBL] [Abstract][Full Text] [Related]
15. Automatic normalized digital color staining in the recognition of abnormal blood cells using generative adversarial networks.
Barrera K; Rodellar J; Alférez S; Merino A
Comput Methods Programs Biomed; 2023 Oct; 240():107629. PubMed ID: 37301181
[TBL] [Abstract][Full Text] [Related]
16. Plant Disease Detection Using Generated Leaves Based on DoubleGAN.
Zhao Y; Chen Z; Gao X; Song W; Xiong Q; Hu J; Zhang Z
IEEE/ACM Trans Comput Biol Bioinform; 2022; 19(3):1817-1826. PubMed ID: 33534712
[TBL] [Abstract][Full Text] [Related]
17. Exploiting the Generative Adversarial Network Approach to Create a Synthetic Topography Corneal Image.
Jameel SK; Aydin S; Ghaeb NH; Majidpour J; Rashid TA; Salih SQ; JosephNg PS
Biomolecules; 2022 Dec; 12(12):. PubMed ID: 36551316
[TBL] [Abstract][Full Text] [Related]
18. Retinal image synthesis from multiple-landmarks input with generative adversarial networks.
Yu Z; Xiang Q; Meng J; Kou C; Ren Q; Lu Y
Biomed Eng Online; 2019 May; 18(1):62. PubMed ID: 31113438
[TBL] [Abstract][Full Text] [Related]
19. Automated and accurate segmentation of leaf venation networks via deep learning.
Xu H; Blonder B; Jodra M; Malhi Y; Fricker M
New Phytol; 2021 Jan; 229(1):631-648. PubMed ID: 32964424
[TBL] [Abstract][Full Text] [Related]
20. Using deep learning to generate synthetic B-mode musculoskeletal ultrasound images.
Cronin NJ; Finni T; Seynnes O
Comput Methods Programs Biomed; 2020 Nov; 196():105583. PubMed ID: 32544777
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]