Results 31 to 40 of about 252,636 (309)

On Data Augmentation for GAN Training [PDF]

IEEE Transactions on Image Processing, 2021
Accepted in IEEE Transactions on Image ...
Ngoc-Trung Tran, Viet-Hung Tran, Ngoc-Bao Nguyen, Trung-Kien Nguyen, Ngai-Man Cheung   +4 more
openaire   +3 more sources

Diffeomorphic transforms for data augmentation [PDF]

, 2022
openL’incremento dei dati è una tecnica ampiamente utilizzata in molti compiti di apprendimento automatico, come la classificazione delle immagini, per ampliare virtualmente la dimensione di dati ed evitare l’overfitting.
COCCO, ALESSIO
core  

PENDUGAAN DATA HILANG DENGAN MENGGUNAKAN DATA AUGMENTATION

Media Statistika, 2011
Data augmentation is a method for estimating missing data. It is a special case of Gibbs sampling which has two important steps. The first step is imputation or I-step where the missing data is generated based on the conditional distributions for missing
Mesra Nova, Moch. Abdul Mukid
doaj   +1 more source

Augmentation leak-prevention scheme using an auxiliary classifier in GAN-based image generation

Journal of King Saud University: Computer and Information Sciences, 2023
Although a generative adversarial network (GAN) can generate realistic and distinct images, it requires numerous training data. Data augmentation is a popular method of incrementing data using various augmentation operations.
Jonghwa Shim, Hyeonwoo Kim, Eunbeen Kim, Eenjun Hwang   +3 more
doaj   +1 more source

Virtual data augmentation method for reaction prediction in small dataset scenario

, 2022
To improve the performance of data-driven reaction prediction models, a new data augmentation method for augmenting data volumes is presented that aims to add fake data in training dataset.
Yejian, Wu, Jiahui, Yu, Yun, Zhang, Hongliang, Duan, Xinqiao, Wang, Zhipeng, Wu, Xinyi, Wu, Chengyun, Zhang, Haoran, Qiao   +8 more
core   +1 more source

Unsupervised learning using topological data augmentation

Physical Review Research, 2020
Unsupervised machine learning is a cornerstone of artificial intelligence as it provides algorithms capable of learning tasks, such as classification of data, without explicit human assistance.
Oleksandr Balabanov, Mats Granath
doaj   +1 more source

Cross Data Set Generalization of Ultrasound Image Augmentation using Representation Learning: A Case Study

Current Directions in Biomedical Engineering, 2021
Data augmentation is a common method to make deep learning assessible on limited data sets. However, classical image augmentation methods result in highly unrealistic images on ultrasound data.
Wulff Daniel, Mehdi Mohamad, Ernst Floris, Hagenah Jannis   +3 more
doaj   +1 more source

Medical Augmentation (Med-Aug) for Optimal Data Augmentation in Medical Deep Learning Networks

Sensors, 2021
Deep learning (DL) algorithms have become an increasingly popular choice for image classification and segmentation tasks; however, their range of applications can be limited.
Justin Lo, Jillian Cardinell, Alejo Costanzo, Dafna Sussman   +3 more
doaj   +1 more source

augmentation data for DAISM

, 2022
The purified dataset for data augmentation for DAISM-DNNXMBD can be downloaded from this repository.The pbmc8k dataset downloaded from 10X Genomics were processed and uesd for data augmentation to create training datasets for training DAISM-DNN models ...
Lin, Y (via Mendeley Data)
core   +1 more source

Data augmentation using Generative Adversarial Networks (GANs) for GAN-based detection of Pneumonia and COVID-19 in chest X-ray images

Informatics in Medicine Unlocked, 2021
Successful training of convolutional neural networks (CNNs) requires a substantial amount of data. With small datasets, networks generalize poorly. Data Augmentation techniques improve the generalizability of neural networks by using existing training ...
Saman Motamed, Patrik Rogalla, Farzad Khalvati   +2 more
doaj   +1 more source