An empirical survey of data augmentation for time series classification with neural networks

Fast multi-language LSTM-based online handwriting recognition

(2020) Victor Carbune et al.   International Journal on Document Analysis and Recognition

Data augmentation approaches for improving animal audio classification

(2020) Loris Nanni et al.   Ecological Informatics

ECG Identification For Personal Authentication Using LSTM-Based Deep Recurrent Neural Networks

(2020) Beom-Hun Kim et al.   SENSORS

Time series classification using local distance-based features in multi-modal fusion networks

(2019) Brian Kenji Iwana et al.   PATTERN RECOGNITION

Data Augmentation with Suboptimal Warping for Time-Series Classification

(2019) Krzysztof Kamycki et al.   SENSORS

Arrhythmia Detection Using Gated Recurrent Unit Network with ECG Signals

(2019) Gang Xu et al.   Journal of Medical Imaging and Health Informatics

LSTM Fully Convolutional Networks for Time Series Classification

(2018) Fazle Karim et al.   IEEE Access

Feature Representation and Data Augmentation for Human Activity Classification Based on Wearable IMU Sensor Data Using a Deep LSTM Neural Network

(2018) Odongo Steven Eyobu et al.   SENSORS

Measuring the class-imbalance extent of multi-class problems

(2017) Jonathan Ortigosa-Hernández et al.   PATTERN RECOGNITION LETTERS

ImageNet Large Scale Visual Recognition Challenge

(2015) Olga Russakovsky et al.   INTERNATIONAL JOURNAL OF COMPUTER VISION

Deep learning in neural networks: An overview

(2015) Jürgen Schmidhuber   NEURAL NETWORKS

A Parsimonious Mixture of Gaussian Trees Model for Oversampling in Imbalanced and Multimodal Time-Series Classification

(2014) Hong Cao et al.   IEEE Transactions on Neural Networks and Learning Systems

DBSMOTE: Density-Based Synthetic Minority Over-sampling TEchnique

(2011) Chumphol Bunkhumpornpat et al.   APPLIED INTELLIGENCE

A global averaging method for dynamic time warping, with applications to clustering

(2010) François Petitjean et al.   PATTERN RECOGNITION

80 Million Tiny Images: A Large Data Set for Nonparametric Object and Scene Recognition

(2008) A. Torralba et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE