DeepAI AI Chat
Log In Sign Up

Similarity Learning based Few Shot Learning for ECG Time Series Classification

by   Priyanka Gupta, et al.
BITS Pilani

Using deep learning models to classify time series data generated from the Internet of Things (IoT) devices requires a large amount of labeled data. However, due to constrained resources available in IoT devices, it is often difficult to accommodate training using large data sets. This paper proposes and demonstrates a Similarity Learning-based Few Shot Learning for ECG arrhythmia classification using Siamese Convolutional Neural Networks. Few shot learning resolves the data scarcity issue by identifying novel classes from very few labeled examples. Few Shot Learning relies first on pretraining the model on a related relatively large database, and then the learning is used for further adaptation towards few examples available per class. Our experiments evaluate the performance accuracy with respect to K (number of instances per class) for ECG time series data classification. The accuracy with 5- shot learning is 92.25 also compare the performance of our method against other well-established similarity learning techniques such as Dynamic Time Warping (DTW), Euclidean Distance (ED), and a deep learning model - Long Short Term Memory Fully Convolutional Network (LSTM-FCN) with the same amount of data and conclude that our method outperforms them for a limited dataset size. For K=5, the accuracies obtained are 57 SCNN, respectively.


page 1

page 2

page 3

page 4


LETS-GZSL: A Latent Embedding Model for Time Series Generalized Zero Shot Learning

One of the recent developments in deep learning is generalized zero-shot...

Metric-Based Few-Shot Learning for Video Action Recognition

In the few-shot scenario, a learner must effectively generalize to unsee...

Condition Assessment of Stay Cables through Enhanced Time Series Classification Using a Deep Learning Approach

This study proposes a data-driven method that detects cable damage from ...

Modeling Time Series Similarity with Siamese Recurrent Networks

Traditional techniques for measuring similarities between time series ar...

Dynamic Spectrum Matching with One-shot Learning

Convolutional neural networks (CNN) have been shown to provide a good so...

Multi-Year Vector Dynamic Time Warping Based Crop Mapping

Recent automated crop mapping via supervised learning-based methods have...

Few Shot Learning with Simplex

Deep learning has made remarkable achievement in many fields. However, l...