| Identification of maize leaves infected by fall armyworms using UAV-based imagery and convolutional neural networks FS Ishengoma, IA Rai, SR Ngoga Computers and Electronics in Agriculture 184, 106124, 2021 | 58 | 2021 |
| Hybrid convolution neural network model for a quicker detection of infested maize plants with fall armyworms using UAV-based images FS Ishengoma, IA Rai, SR Ngoga Ecological Informatics, DOI: 10.1016/j.ecoinf.2021.101502, 2021 | 23 | 2021 |
| Internet of things to improve agriculture in sub sahara Africa-a case study FS Ishengoma, M Athuman IJASRE, 2018 | 8 | 2018 |
| Integrating Pattern Recognition and CNN-based Models for Improved Bean Disease Detection and Agricultural Yield Enhancement FS Ishengoma, NN Lymo | | 2024 |
| Design of a low-cost IoT-based wearable system for cardiovascular disease detection and monitoring in Rwanda K Sumwiza, C Twizere, G Rushingabigwi, P Bakunzibake, FS Ishengoma 3rd IEEE International Conference on Signal, Control and Communication (SCC …, 2024 | | 2024 |
| Autonomous System for Locating the Maize Plant Infected by Fall Armyworm FS Ishengoma, IA Rai, I Gatare 12th Computer Science Conference 724, 106–113, 2023 | | 2023 |
| Grape Disease Evaluation Using a Mixed-Model Ensemble of Convolution Neural Network and Random Forest FS Ishengoma, NN Lyimo | | 2023 |
| Contrast enhancement of UAV-based maize plant images for automatic detection of fall armyworm FS Ishengoma, IA Rai, I Gatare 6th Computational Methods in Systems and Software 597 (No 1), 100-107, 2023 | | 2023 |
Idris A. RaiState University of Zanzibar (SUZA)Verified email at suza.ac.tz
