School of Computing and IT (JA)

Comparative Analysis of Deep Learning Models for Crop Diseases and Pest Classification

Ochango, Vincent Mbandu; Wambugu, Geoffrey Mariga; Oirere, Aaron Mogeni (International Journal of Formal Sciences: Current and Future Research Trends (IJFSCFRT), 2025)

The deep learning models for crop diseases and pest classification research examined how deep learning might improve farming methods, particularly to accurately classify pests and diseases that affect crops. The importance ...

Comparative Analysis of Machine Learning Algorithms Accuracy for Maize Leaf Disease Identification

Ochango, Vincent Mbandu; Wambugu, Geoffrey Mariga; Ndia, John Gichuki (nternational Journal of Formal Sciences: Current and Future Research Trends (IJFSCFRT), 2023)

The number of data points predicted correctly out of the total data points is known as accuracy in image classification models. Assessment of the accuracy is very important since it compares the correct images to the ones ...

A Model for Face Recognition using EigenFace Algorithm

Ochango, Vincent Mbandu (International Journal of Formal Sciences: Current and Future Research Trends, 2023)

The use of a computer to recognize a person by the means of their face is what is known as face recognition in artificial intelligence. The term biometrics is an umbrella term that includes face recognition as well as ...

Architecture of Deep Learning Algorithms in Image Classification: Systematic Literature Review

Ochango, Vincent Mbandu; Ndia, John Gichuki (International Journal of Formal Sciences: Current and Future Research Trends (IJFSCFRT), 2023)

The development of deep learning algorithms has led to major improvements in image classification, a key problem in computer vision. In this study, the researcher provide an in-depth analysis of the various deep learning ...

An Empirical Analysis of Encoder Decoder (U Net) Variants for Medical Image Segmentation

Kamiri, Jackson; Wambugu, Geoffrey Mariga; Oirere, Aaron Mogeni (International Journal of Scientific Research in Computer Science and Engineering, 2025)

U-Net convolutional neural networks have become a cornerstone in medical image processing, particularly for complex segmentation tasks. However, with the proliferation of various U-Net variants, it is imperative to evaluate ...

Deep Learning Model for Crop Diseases and Pest Classification

Ochango, Vincent Mbandu; Wambugu,Geoffrey Mariga; Oirere, Aaron Mogeni (International Journal of Computer and Information Technology, 2024)

The study on deep learning models for crop diseases and pest classification looked at how these models may enhance agricultural practices, specifically for the purpose of more precise pest and crop disease classification. ...

Feature Extraction using Histogram of Oriented Gradients for Image Classification in Maize Leaf Diseases

Ochango, Vincent M; Wambugu, Geoffrey M; Ndia, John G (International Journal of Computer and Information Technology, 2022)

The paper presents feature extraction methods and classification algorithms used to classify maize leaf disease images. From maize disease images, features are extracted and passed to the machine learning classification ...

Quick Response Code Security Attacks and Countermeasures: A Systematic Literature Review

Njuguna, David; Ndia, John G (Journal of Cyber Security, 2025)

A quick response code is a barcode that allows users to instantly access information via a digital device. Quick response codes store data as pixels in a square-shaped grid. QR codes are prone to cyber-attacks. This ...

A Reinforcement Learning-Based Multi-Agent System for Advanced Network Attack Prediction

Wanjau, Stephen K; Thiiru, Stephen N (International Journal of Scientific Research in Computer Science and Engineering, 2024)

This paper addresses the challenges of traditional Network Intrusion Detection Systems (NIDS) in handling the increasing complexity and volume of modern cyberattacks. The authors suggest a novel multi-agent deep reinforcement ...

Trust Attributes in Multi-Path Congestion Avoidance Techniques to Curb Wormhole Attacks in Wireless Sensor Networks

Mwihaki, Fortine Mata; Muketha, Geoffrey Muchiri; Kamau, Gabriel Ndung’u (Journal of Computer Networks,, 2024)

Wireless sensor networks (WSNs) have become widespread in recent years due to their uses in healthcare, infrastructure monitoring, environmental sensing, tactical surveillance, and defense. However, their inherent ...

A Framework for Analyzing UML Behavioral Metrics based on Complexity Perspectives

King’ori, Ann Wambui; Muketha, Geoffrey Muchiri.;; Ndia, John Gichuki (International Journal of Software Engineering (IJSE), 2024)

As software systems become more complex, software modeling is crucial. Software engineers are adopting UML behavioral diagrams to model the dynamic features of a system. These dynamic diagrams keep changing for further ...

Multi-task Deep Learning in Medical Image Processing: A Systematic Review

Kamiri, Jackson; Wambugu, Geoffrey M; Oirere, Aaron M. (International Journal of Computing Sciences Research, 2025-01)

Purpose — Multi-task learning (MTL) is a deep learning approach that aims to jointly learn two or more tasks with the goal of leveraging shared knowledge among the tasks. This study aimed to review existing MTL models in ...

A Comparative Study of Transformer-based Models for Hate-Speech Detection in English-Kiswahili Code-Switched Social Media Text

Ng’ang’a, Njung’e Fredrick.; Oirere, Aaron M.; Ndung'u, Rachel N. (International Journal of Advanced Trends in Computer Science and Engineering, 2024)

The transformer architecture, first introduced in 2017 by researchers at Google, has revolutionized natural language processing in various tasks, including text classification. This architecture formed the basis of future ...