Multimodal CNN–LSTM Framework for Real-Time Maize Disease Detection
- DOI
- 10.28989/avitec.v8i2.3970
- Published
- 2026-06-03
- Container
- Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC)
- Publisher
- Institut Teknologi Dirgantara Adisutjipto (ITDA)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.28989/avitec.v8i2.3970,
title = {Multimodal CNN–LSTM Framework for Real-Time Maize Disease Detection},
author = {Mercy Chepkoech Tonui and John Kamau and Raymond Wafula Ongus},
year = {2026},
journal = {Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC)},
doi = {10.28989/avitec.v8i2.3970},
url = {https://doi.org/10.28989/avitec.v8i2.3970}
}RIS
TY - JOUR TI - Multimodal CNN–LSTM Framework for Real-Time Maize Disease Detection AU - Mercy Chepkoech Tonui AU - John Kamau AU - Raymond Wafula Ongus PY - 2026 JO - Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC) DO - 10.28989/avitec.v8i2.3970 UR - https://doi.org/10.28989/avitec.v8i2.3970 ER -
APA
Tonui, M. C., Kamau, J., & Ongus, R. W. (2026). Multimodal CNN–LSTM Framework for Real-Time Maize Disease Detection. Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC). https://doi.org/10.28989/avitec.v8i2.3970
Source records
- crossref · retrieved 2026-09-26T03:41:18.067Z