Neonatal Pain Expression Recognition Using Transfer Learning

by   Ghada Zamzmi, et al.

Transfer learning using pre-trained Convolutional Neural Networks (CNNs) has been successfully applied to images for different classification tasks. In this paper, we propose a new pipeline for pain expression recognition in neonates using transfer learning. Specifically, we propose to exploit a pre-trained CNN that was originally trained on a relatively similar dataset for face recognition (VGG Face) as well as CNNs that were pre-trained on a relatively different dataset for image classification (iVGG F,M, and S) to extract deep features from neonates' faces. In the final stage, several supervised machine learning classifiers are trained to classify neonates' facial expression into pain or no pain expression. The proposed pipeline achieved, on a testing dataset, 0.841 AUC and 90.34 accuracy, which is approx. 7 higher than the accuracy of handcrafted traditional features. We also propose to combine deep features with traditional features and hypothesize that the mixed features would improve pain classification performance. Combining deep features with traditional features achieved 92.71 accuracy and 0.948 AUC. These results show that transfer learning, which is a faster and more practical option than training CNN from the scratch, can be used to extract useful features for pain expression recognition in neonates. It also shows that combining deep features with traditional handcrafted features is a good practice to improve the performance of pain expression recognition and possibly the performance of similar applications.


page 1

page 2

page 3

page 4


Pre-Trained Convolutional Neural Network Features for Facial Expression Recognition

Facial expression recognition has been an active area in computer vision...

Learning to Select Pre-Trained Deep Representations with Bayesian Evidence Framework

We propose a Bayesian evidence framework to facilitate transfer learning...

FaceNet2ExpNet: Regularizing a Deep Face Recognition Net for Expression Recognition

Relatively small data sets available for expression recognition research...

Winter Road Surface Condition Recognition Using A Pretrained Deep Convolutional Network

This paper investigates the application of the latest machine learning t...

Tool and Phase recognition using contextual CNN features

A transfer learning method for generating features suitable for surgical...

Deep Learning for Identifying Iran's Cultural Heritage Buildings in Need of Conservation Using Image Classification and Grad-CAM

The cultural heritage buildings (CHB), which are part of mankind's histo...

Deep Collaborative Weight-based Classification

One of the biggest problems in deep learning is its difficulty to retain...

Please sign up or login with your details

Forgot password? Click here to reset