Results 41 to 50 of about 24,031,398 (300)

Data Augmentation and Transfer Learning Strategies for Reaction Prediction in Low Chemical Data Regimes [PDF]

, 2020
: Effective and rapid deep learning method to predict chemical reactions contributes to the research and development of organic chemistry and drug discovery.
Yun, Zhang, Hongliang, Duan, Xinqiao, Wang, Jiamin, Ge, Chengyun, Zhang, Jing, Tang, Ling, Wang, An, Su   +7 more
core   +1 more source

Text Data Augmentation Using Generative Adversarial Networks – A Systematic Review [PDF]

, 2023
Insufficient data is one of the main drawbacks in natural language processing tasks, and the most prevalent solution is to collect a decent amount of data that will be enough for the optimisation of the model.
Silva, Kanishka, Kanishka Silva, Kanishka Silva, Blain, Frederic; id_orcid, Can, Burcu, Sarwar, Raheem, Blain, Frederic, Mitkov, Ruslan   +6 more
core   +1 more source

Hyperspectral Data Augmentation

CoRR, 2019
Submitted to IEEE Geoscience and Remote Sensing ...
Jakub Nalepa, Michal Myller, Michal Kawulok   +2 more
openaire   +2 more sources

Differentiable Data Augmentation with Kornia

CoRR, 2020
In this paper we present a review of the Kornia [1, 2] differentiable data augmentation (DDA) module for both for spatial (2D) and volumetric (3D) tensors. This module leverages differentiable computer vision solutions from Kornia, with an aim of integrating data augmentation (DA) pipelines and strategies to existing PyTorch components (e.g.
Shi, Jian, Riba Pi, Edgar, Mishkin, Dmytro, Moreno-Noguer, Francesc, Nicolaou, Anguelos   +4 more
openaire   +4 more sources

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

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

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

DIFFEOMORPHIC TRANSFORMS FOR DATA AUGMENTATION OF HIGHLY VARIABLE SHAPE AND TEXTURE OBJECTS [PDF]

, 2022
openIn questo documento viene analizzata una nuova tecnica utilizzata in ambito di Data Augmentation che pone le proprie basi sul morphing. L’addestramento di reti neurali convoluzionali (CNN) richiede una grossa mole di dati, i quali possono essere ...
LAZZARIN, FILIPPO
core  

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

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