| Dynamic fine‐tuning layer selection using Kullback–Leibler divergence RN Wanjiku, L Nderu, M Kimwele Engineering Reports 5 (5), e12595, 2023 | 6 | 2023 |
| Scoped class cohesion metric for software process assessment R Wanjiku, G Okeyo, W Cheruiyot International Journal of Computer Science Issues (IJCSI) 13 (2), 12, 2016 | 3 | 2016 |
| Improved transfer learning using textural features conflation and dynamically fine-tuned layers RN Wanjiku, L Nderu, M Kimwele PeerJ Computer Science 9, e1601, 2023 | 1 | 2023 |
| Dynamic pre-trained models layer selection using filter-weights cosine similarity R Wanjiku, L Nderu, M Kimwele Pan-African Artificial Intelligence and Smart Systems Conference, 95-108, 2022 | 1 | 2022 |
| Feature-Instance Based Fine-Tuning In Transfer Learning Model RN Wanjiku JKUAT-COPAS, 2024 | | 2024 |
| Transfer learning data adaptation using conflation of low‐level textural features RN Wanjiku, L Nderu, M Kimwele Engineering Reports 5 (5), e12603, 2023 | | 2023 |
| Improved Medical Imaging Transfer Learning through the Conflation of Domain Features R Wanjiku, L Nderu, M Kimwele International Conference on Technological Advancement in Embedded and Mobile …, 2022 | | 2022 |
| SOFTWARE PRODUCT QUALITY ASSESSMENT USING SCOPED CLASS COHESION METRIC (SCCM) RN WANJIKU juat pure science, 2017 | | 2017 |
Lawrence Nderu (PhD)Department of Computing, School of Computing and Information Technology, JKUAT在 jkuat.ac.ke 的电子邮件经过验证
