| An optimum tea fermentation detection model based on deep convolutional neural networks G Kimutai, A Ngenzi, RN Said, A Kiprop, A Förster Data 5 (2), 44, 2020 | 14 | 2020 |
| An internet of things (IoT)-based optimum tea fermentation detection model using convolutional neural networks (CNNs) and majority voting techniques G Kimutai, A Ngenzi, S Rutabayiro Ngoga, RC Ramkat, A Förster Journal of Sensors and Sensor Systems 10 (2), 153-162, 2021 | 4 | 2021 |
| A Data Descriptor for Black Tea Fermentation Dataset G Kimutai, A Ngenzi, R Ngoga Said, RC Ramkat, A Förster Data 6 (3), 34, 2021 | 3 | 2021 |
| Offloading an Energy-Efficient IoT Solution to the Edge: A Practical Solution for Developing Countries G Kimutai, A Ngenzi, SR Ngoga, A Forster 2021 IEEE Global Humanitarian Technology Conference (GHTC), 265-272, 2021 | 2 | 2021 |
| A Content Based Image Retrieval Model for E-Commerce G Kimutai, W Cheruiyot, C Otieno International Journal of Engineering and Computer Science, 2018 | 2 | 2018 |
| An instance-based deep transfer learning approach for resource-constrained environments G Kimutai, A Förster Proceedings of the ACM SIGCOMM Workshop on Networked Sensing Systems for a …, 2022 | | 2022 |
| A Retail Agro-Vet Application System: A Case of a Kenyan Agro-Vet G Kimutai, A Ngenzi, A Kiprop | | 2019 |
| Application of Computing Techniques in Monitoring Black Tea Processing for Improved Quality: Review and Future Directions G Kimutai, A Ngenzi, RN Said, R Ramkat | | 2019 |
| A Retail Agro-V et Application System: A Case of a Kenyan Agro-V et G Kimutai, A Ngenzi, A Kiprop International Journal of Computer Science and Mobile Computing, 2019 | | 2019 |
Dr. Alexander NGENZIProfessor of Computer Science and EngineeringVerified email at ur.ac.rw
