A Hybrid Neuromorphic Object Tracking and Classification Framework for Real-Time Systems
- DOI
- 10.1109/tnnls.2023.3243679
- Published
- 2024-08
- Container
- IEEE Transactions on Neural Networks and Learning Systems
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1109/tnnls.2023.3243679,
title = {A Hybrid Neuromorphic Object Tracking and Classification Framework for Real-Time Systems},
author = {Andrés Ussa and Chockalingam Senthil Rajen and Tarun Pulluri and Deepak Singla and Jyotibdha Acharya and Gideon Fu Chuanrong and Arindam Basu and Bharath Ramesh},
year = {2024},
journal = {IEEE Transactions on Neural Networks and Learning Systems},
doi = {10.1109/tnnls.2023.3243679},
url = {https://doi.org/10.1109/tnnls.2023.3243679}
}RIS
TY - JOUR TI - A Hybrid Neuromorphic Object Tracking and Classification Framework for Real-Time Systems AU - Andrés Ussa AU - Chockalingam Senthil Rajen AU - Tarun Pulluri AU - Deepak Singla AU - Jyotibdha Acharya AU - Gideon Fu Chuanrong AU - Arindam Basu AU - Bharath Ramesh PY - 2024 JO - IEEE Transactions on Neural Networks and Learning Systems DO - 10.1109/tnnls.2023.3243679 UR - https://doi.org/10.1109/tnnls.2023.3243679 ER -
APA
Ussa, A., Rajen, C. S., Pulluri, T., Singla, D., Acharya, J., Chuanrong, G. F., Basu, A., & Ramesh, B. (2024). A Hybrid Neuromorphic Object Tracking and Classification Framework for Real-Time Systems. IEEE Transactions on Neural Networks and Learning Systems. https://doi.org/10.1109/tnnls.2023.3243679
Source records
- crossref · retrieved 2026-11-07T21:26:53.063Z