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Found 9 papers, 0 papers with code
Robust Neonatal Face Detection in Real-world Clinical Settings
Current face detection algorithms are extremely generalized and can obtain decent accuracy when detecting the adult faces.
Pattern Recognition in Vital Signs Using Spectrograms
The results from the proposed approach are promising with an accuracy of 91. 55% and 91. 67% in prediction and classification tasks respectively.
Multimodal Spatio-Temporal Deep Learning Approach for Neonatal Postoperative Pain Assessment
We compare the performance of the multimodal and unimodal postoperative pain assessment, and measure the impact of temporal information integration.
First Investigation Into the Use of Deep Learning for Continuous Assessment of Neonatal Postoperative Pain
This paper presents the first investigation into the use of fully automated deep learning framework for assessing neonatal postoperative pain.
Harnessing the Power of Deep Learning Methods in Healthcare: Neonatal Pain Assessment from Crying Sound
Neonatal pain assessment in clinical environments is challenging as it is discontinuous and biased.
Multi-Channel Neural Network for Assessing Neonatal Pain from Videos
Neonates do not have the ability to either articulate pain or communicate it non-verbally by pointing.
Contrast Enhancement of Medical X-Ray Image Using Morphological Operators with Optimal Structuring Element
To guide surgical and medical treatment X-ray images have been used by physicians in every modern healthcare organization and hospitals.
Cooking State Recognition from Images Using Inception Architecture
In this paper, we propose a deep learning approach to identify different cooking states from images for a kitchen robot.
Identifying Object States in Cooking-Related Images
The trained state identification model is evaluated on a subset of the Imagenet dataset and state labels are provided using a combination of the model with manual checking.
