School of Pure and Applied Sciences
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Item Deep Transfer Learning Optimization Techniques for Medical Image Classification: A Review(2022) Kariuki, Paul Wahome; Gikunda, Patrick Kinyua; Wandeto, John MwangiMedical image classification is a complex and challenging task due to the heterogeneous nature of medical data. Deep transfer learning has emerged as a promising technique for medical image classification, allowing the leveraging of knowledge from pre-trained models learned from large-scale datasets, resulting in improved performance with minimal training and overcoming the disadvantage of small data sets. This paper concisely overviews cutting-edge deep transfer learning optimization approaches for medical image classification. The study covers convolutional neural networks and transfer learning techniques, including relation-based, feature-based, parameter-based, and instance-based transfer learning. Classical classifiers such as Resnet, VGG, Alexnet, Googlenet, and Inception are examined, and their performance on medical image classification tasks is compared. The paper also discusses optimization techniques, such as batch normalization, regularization, and weight initialization, as well as data augmentation and kernel mathematical formulations. The study concludes by identifying challenges when using deep transfer learning for medical image classification and proposing potential future approaches for this field.Item Factors Inhibiting the Implementation of Digital Villages in Kenya(2017) Karume, Simon; Shisoka, Dorcus ArshleyThe achievement of an information-based society is one of the main priorities of the Government of Kenya (GoK) towards the realization of national development goals and objectives for wealth and employment creation. However, even in their efforts the ICT sector is still currently more active in urban areas, resulting in wide regional disparities in the distribution of ICT facilities. In order to address this disparity, the Kenya ICT Board (KICTB) supported the roll out of new “electronic centre’s” which were named Pasha Centre’s (and are also commonly referred to as Digital Villages).The Digital village’s initiatives in Kenya commenced with a lot of optimism in 2009 however five years down the line it cannot be recorded that they have been successful. The purpose of this study was to establish the factors that have hindered the successful implementation of digital villages in Kenya. For this study desk research methodology was adopted. The secondary data from published reports was discussed with emphasis on the area of interest to this study. The findings of this study indicated that there were various factors that hindered the successful implementation of digital villages in Kenya. The study recommended need for having a government policy for the digital village project. This policy if developed will serve to protect such projects in future enabling them to take off and function independently.Collection Collection Collection