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Dina Machuve
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2020 – today
- 2023
- [j5]Elena Falcettoni, Dina Machuve, Bryan Wilder, Angela Zhou:
Report on the 2nd ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO 2022). SIGecom Exch. 21(1): 14-19 (2023) - 2022
- [j4]Dina Machuve, Ezinne Nwankwo, Neema Mduma, Jimmy T. Mbelwa:
Poultry diseases diagnostics models using deep learning. Frontiers Artif. Intell. 5 (2022) - [j3]Dina Machuve, Ezinne Nwankwo, Neema Mduma, Jimmy T. Mbelwa:
Corrigendum: Poultry diseases diagnostics models using deep learning. Frontiers Artif. Intell. 5 (2022) - 2021
- [j2]Loyani K. Loyani, Karen L. Bradshaw, Dina Machuve:
Segmentation of Tuta Absoluta's Damage on Tomato Plants: A Computer Vision Approach. Appl. Artif. Intell. 35(14): 1107-1127 (2021) - [c5]Rambo Hilary, Dina Machuve, Silas Mirau:
Mobile Application for Gate Pass Management System Enhancement. AFRICON 2021: 1-5 - [c4]Ivan Koojo, Dina Machuve, Silas Mirau, Simon Peter Miyingo:
Design of a Passenger Security and Safety System for the Kayoola EVs Bus. AFRICON 2021: 1-6 - [c3]Beatus Mbunda, Dina Machuve, Silas Mirau:
Warehouse Management System Enhancement: A Case Study of ATOZ Textiles Limited. AFRICON 2021: 1-5 - [c2]Neema Mduma, Dina Machuve:
Machine Learning Model for Predicting Student Dropout: A Case of Tanzania, Kenya and Uganda. AFRICON 2021: 1-6 - [c1]Mbonimpaye John, Beatus Mbunda, Victor Willa, Neema Mduma, Dina Machuve, Shubi Felix Kaijage:
Document Digitization Technology and Its Application in Tanzania. IntelliSys (2) 2021: 716-723 - 2020
- [i2]Sophia Sanga, Victor Mero, Dina Machuve, Davis Mwanganda:
Mobile-Based Deep Learning Models for Banana Diseases Detection. CoRR abs/2004.03718 (2020) - [i1]Yannis Kalantidis, Laura Sevilla-Lara, Ernest Mwebaze, Dina Machuve, Hamed Alemohammad, David Guerena:
Proceedings of the ICLR Workshop on Computer Vision for Agriculture (CV4A) 2020. CoRR abs/2004.11051 (2020)
2010 – 2019
- 2019
- [j1]Neema Mduma, Khamisi Kalegele, Dina Machuve:
A Survey of Machine Learning Approaches and Techniques for Student Dropout Prediction. Data Sci. J. 18: 14 (2019)
Coauthor Index
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