Cargando…
HEMIGEN: Human Embryo Image Generator Based on Generative Adversarial Networks
We propose a method for generating the synthetic images of human embryo cells that could later be used for classification, analysis, and training, thus resulting in the creation of new synthetic image datasets for research areas lacking real-world data. Our focus was not only to generate the generic...
Autores principales: | Dirvanauskas, Darius, Maskeliūnas, Rytis, Raudonis, Vidas, Damaševičius, Robertas, Scherer, Rafal |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6720205/ https://www.ncbi.nlm.nih.gov/pubmed/31426441 http://dx.doi.org/10.3390/s19163578 |
Ejemplares similares
-
Deep Learning Based Evaluation of Spermatozoid Motility for Artificial Insemination
por: Valiuškaitė, Viktorija, et al.
Publicado: (2020) -
HUMANNET—A Two-Tiered Deep Neural Network Architecture for Self-Occluding Humanoid Pose Reconstruction
por: Kulikajevas, Audrius, et al.
Publicado: (2021) -
Deep Convolutional Neural Network-Based Visual Stimuli Classification Using Electroencephalography Signals of Healthy and Alzheimer’s Disease Subjects
por: Komolovaitė, Dovilė, et al.
Publicado: (2022) -
Detection of sitting posture using hierarchical image composition and deep learning
por: Kulikajevas, Audrius, et al.
Publicado: (2021) -
Multi-Modal Brain Tumor Detection Using Deep Neural Network and Multiclass SVM
por: Maqsood, Sarmad, et al.
Publicado: (2022)