Neural Network Architecture for Database Augmentation Using Shared Features

2 February 2023

Papers citing "Neural Network Architecture for Database Augmentation Using Shared Features"

9 / 9 papers shown

Title
Combining datasets to increase the number of samples and improve model fitting Thu Nguyen Rabindra Khadka Nhan Phan Anis Yazidi Pål Halvorsen Michael A. Riegler AI4TS 59 5 0 11 Oct 2022
An overview of mixing augmentation methods and augmentation strategies Dominik Lewy Jacek Mańdziuk 42 61 0 21 Jul 2021
DeepSMOTE: Fusing Deep Learning and SMOTE for Imbalanced Data Damien Dablain Bartosz Krawczyk Nitesh Chawla 59 270 0 05 May 2021
CSMOUTE: Combined Synthetic Oversampling and Undersampling Technique for Imbalanced Data Classification Michał Koziarski 18 31 0 07 Apr 2020
Neural Network Based Undersampling Techniques Md. Adnan Arefeen Sumaiya Tabassum Nimi Mohammad Sohel Rahman 26 41 0 18 Aug 2019
Oversampling for Imbalanced Learning Based on K-Means and SMOTE F. Last G. Douzas F. Bação 48 747 0 02 Nov 2017
A systematic study of the class imbalance problem in convolutional neural networks Mateusz Buda A. Maki Maciej A. Mazurowski 189 2,352 0 15 Oct 2017
VIGAN: Missing View Imputation with Generative Adversarial Networks Chao Shang A. Palmer Jiangwen Sun Ko-Shin Chen Jin Lu J. Bi GAN 41 121 0 22 Aug 2017
SMOTE: Synthetic Minority Over-sampling Technique Nitesh Chawla Kevin W. Bowyer Lawrence Hall W. Kegelmeyer AI4TS 329 25,569 0 09 Jun 2011