CribNet: Enhancing Infant Safety in Cribs Through Vision-Based Hazard Detection-Reference-Cited by-同舟云学术

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CribNet: Enhancing Infant Safety in Cribs Through Vision-Based Hazard Detection

Published:2024-05-27 Issue: Volume:2 Page:01-08
ISSN:
Container-title:2024 IEEE 18th International Conference on Automatic Face and Gesture Recognition (FG)
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Author:

Zhu Shaotong¹,Mathew Amal¹,Hatamimajoumerd Elaheh¹,Wan Michael²,Taylor Briana³,Venkatesaramani Rajagopal⁴,Ostadabbas Sarah¹

Affiliation:

1. Northeastern University,Department of Electrical and Computer Engineering,Boston,MA,USA

2. Institute for Experiential AI, Northeastern University,Portland,ME,USA

3. Roux Institute, Northeastern University,Portland,ME,USA

4. Khoury College of Computer Sciences, Northeastern University,Boston,MA,USA

Funder

National Science Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10581880/10581860/10581871.pdf?arnumber=10581871

Reference45 articles.

1. Multiple Toddler Tracking in Indoor Videos

2. YOLACT: Real-Time Instance Segmentation

3. InfoGCN: Representation Learning for Human Skeleton-based Action Recognition

4. Roboflow 100: A rich, multi-domain object detection benchmark;Ciaglia;arXiv preprint,2022

5. Inconsistency Between Pictures on Baby Diaper Packaging in Europe and Safe Infant Sleep Recommendations

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