A Quantitative Comparison of Different Machine Learning Approaches for Human Spermatozoa Quality Prediction Using Multimodal Datasets-Reference-Cited by-同舟云学术

A Quantitative Comparison of Different Machine Learning Approaches for Human Spermatozoa Quality Prediction Using Multimodal Datasets

Published:2020-10-12 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 28th ACM International Conference on Multimedia
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Author:

Feng Ming¹,Xu Kele²,Wang Yin¹

Affiliation:

1. Tongji University, Shanghai, China

2. National University of Defense Technology, Changsha, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3394171.3416285

Reference16 articles.

1. Tadas Baltruvs aitis Chaitanya Ahuja and Louis-Philippe Morency. 2018. Multimodal machine learning: A survey and taxonomy. IEEE transactions on pattern analysis and machine intelligence Vol. 41 2 (2018) 423--443. Tadas Baltruvs aitis Chaitanya Ahuja and Louis-Philippe Morency. 2018. Multimodal machine learning: A survey and taxonomy. IEEE transactions on pattern analysis and machine intelligence Vol. 41 2 (2018) 423--443.

2. XGBoost

3. VISEM

4. ACM Multimedia BioMedia 2020 Grand Challenge Overview

5. Steven A Hicks Jorunn M Andersen Oliwia Witczak Vajira Thambawita Pål Halvorsen Hugo L Hammer Trine B Haugen and Michael A Riegler. 2019. Machine learning-based analysis of sperm videos and participant data for male fertility prediction. Scientific reports Vol. 9 1 (2019) 1--10. Steven A Hicks Jorunn M Andersen Oliwia Witczak Vajira Thambawita Pål Halvorsen Hugo L Hammer Trine B Haugen and Michael A Riegler. 2019. Machine learning-based analysis of sperm videos and participant data for male fertility prediction. Scientific reports Vol. 9 1 (2019) 1--10.

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