SiamBOMB: A Real-Time AI-Based System for Home-Cage Animal Tracking, Segmentation and Behavioral Analysis
Abstract
Biologists often need to handle numerous video-based home-cage animal behavior analysis tasks that require massive workloads. Therefore, we develop an AI-based multi-species tracking and segmentation system, SiamBOMB, for real-time and automatic home-cage animal behavioral analysis. In this system, a background-enhanced Siamese-based network with replaceable modular design ensures the flexibility and generalizability of the system, and a user-friendly interface makes it convenient to use for biologists. This real-time AI system will effectively reduce the burden on biologists.
Cite
Text
Chen et al. "SiamBOMB: A Real-Time AI-Based System for Home-Cage Animal Tracking, Segmentation and Behavioral Analysis." International Joint Conference on Artificial Intelligence, 2020. doi:10.24963/IJCAI.2020/776Markdown
[Chen et al. "SiamBOMB: A Real-Time AI-Based System for Home-Cage Animal Tracking, Segmentation and Behavioral Analysis." International Joint Conference on Artificial Intelligence, 2020.](https://mlanthology.org/ijcai/2020/chen2020ijcai-siambomb/) doi:10.24963/IJCAI.2020/776BibTeX
@inproceedings{chen2020ijcai-siambomb,
title = {{SiamBOMB: A Real-Time AI-Based System for Home-Cage Animal Tracking, Segmentation and Behavioral Analysis}},
author = {Chen, Xi and Zhai, Hao and Liu, Danqian and Li, Weifu and Ding, Chaoyue and Xie, Qiwei and Han, Hua},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2020},
pages = {5300-5302},
doi = {10.24963/IJCAI.2020/776},
url = {https://mlanthology.org/ijcai/2020/chen2020ijcai-siambomb/}
}