Results 31 to 40 of about 207,018 (117)

Data augmentation scheme for federated learning with non-IID data

Tongxin xuebao, 2023
To solve the problem that the model accuracy remains low when the data are not independent and identically distributed (non-IID) across different clients in federated learning, a privacy-preserving data augmentation scheme was proposed.Firstly, a data ...
Lingtao TANG, Di WANG, Shengyun LIU
doaj   +2 more sources

Adversarial Data Augmentation on Breast MRI Segmentation

Applied Sciences, 2021
The scarcity of balanced and annotated datasets has been a recurring problem in medical image analysis. Several researchers have tried to fill this gap employing dataset synthesis with adversarial networks (GANs).
João F. Teixeira, Mariana Dias, Eva Batista, Joana Costa, Luís F. Teixeira, Hélder P. Oliveira   +5 more
doaj   +1 more source

SeisAug: A data augmentation python toolkit

Applied Computing and Geosciences
A common limitation in applying any deep learning and machine learning techniques is the limited labelled dataset which can be addressed through Data augmentation (DA). SeisAug is a DA python toolkit to address this challenge in seismological studies. DA.
D. Pragnath, G. Srijayanthi, Santosh Kumar, Sumer Chopra   +3 more
doaj   +1 more source

Virtual data augmentation method for reaction prediction

Scientific Reports, 2022
To improve the performance of data-driven reaction prediction models, we propose an intelligent strategy for predicting reaction products using available data and increasing the sample size using fake data augmentation.
Xinyi Wu, Yun Zhang, Jiahui Yu, Chengyun Zhang, Haoran Qiao, Yejian Wu, Xinqiao Wang, Zhipeng Wu, Hongliang Duan   +8 more
doaj   +1 more source

A survey on Image Data Augmentation for Deep Learning

Journal of Big Data, 2019
Deep convolutional neural networks have performed remarkably well on many Computer Vision tasks. However, these networks are heavily reliant on big data to avoid overfitting. Overfitting refers to the phenomenon when a network learns a function with very
Connor Shorten, Taghi M. Khoshgoftaar
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GAN Data Augmentation Methods in Rock Classification

Applied Sciences, 2023
In this paper, a data augmentation method Conditional Residual Deep Convolutional Generative Adversarial Network (CRDCGAN) based on Deep Convolutional Generative Adversarial Network (DCGAN) is proposed to address the problem that the accuracy of existing
Gaochang Zhao, Zhao Cai, Xin Wang, Xiaohu Dang   +3 more
doaj   +1 more source

On the Importance of Imbalance‐Aware Evaluation for Edge‐Of‐Field Runoff Prediction: A Commentary on Ford et al. (2022)

Geophysical Research Letters
Field‐scale runoff prediction is critical for managing nutrient losses. Ford et al. (2022, https://doi.org/10.1029/2022gl100667) present an innovative hybrid modeling and regionalization framework that integrates cluster analysis, National Water Model ...
M. S. Jahangir, S. Steinschneider
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Optimizing Rice Plant Disease Classification Using Data Augmentation with GANs on Convolutional Neural Networks

Intensif: Jurnal Ilmiah Penelitian Teknologi dan Penerapan Sistem Informasi
Background: Rice disease classification using CNN models faces challenges due to limited data, particularly in minority classes, and inconsistent image quality, which affect model performance.
Tinuk Agustin, Indrawan Ady Saputro, Mochammad Luthfi Rahmadi   +2 more
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Data Augmentation-Based Photovoltaic Power Prediction

Energies
In recent years, as the grid-connected installed capacity of photovoltaic (PV) power generation has increased by leaps and bounds, it has assumed considerable importance in predicting PV power output.
Xifeng Wang, Yijun Shen, Haiyu Song, Shichao Liu   +3 more
doaj   +1 more source

Survey of Image Data Augmentation Techniques Based on Deep Learning [PDF]

Jisuanji kexue
In recent years,deep learning has demonstrated excellent performance in many computer vision tasks such as image classification,object detection,and image segmentation.Deep neural networks usually rely on a large amount of training data to avoid ...
SUN Shukui, FAN Jing, SUN Zhongqing, QU Jinshuai, DAI Tingting
doaj   +1 more source