Outputs (17)

Maize yield predictive models and mobile-based decision support system for smallholder farmers in Africa (2022)
Presentation / Conference Contribution

Existing machine learning models for crop yield prediction model environmental data on the assumption that soil variables are unaffected by weather variables and therefore learn their intrinsic features independently. If the focus of crop yield predi... Read More about Maize yield predictive models and mobile-based decision support system for smallholder farmers in Africa.

Diabetes mellitus prediction and diagnosis from a data preprocessing and machine learning perspective (2022)
Journal Article

Background and Objective: Diabetes mellitus is a metabolic disorder characterized by hyperglycemia, which results from the inadequacy of the body to secrete and respond to insulin. If not properly managed or diagnosed on time, diabetes can pose a ris... Read More about Diabetes mellitus prediction and diagnosis from a data preprocessing and machine learning perspective.

A robust machine learning framework for diabetes prediction (2021)
Presentation / Conference Contribution

Diabetes mellitus is a metabolic disorder characterized by hyperglycemia which results from the inadequacy of the body to secret and responds to insulin. If not properly managed or diagnosed on time, diabetes can pose a risk to vital body organs such... Read More about A robust machine learning framework for diabetes prediction.

Data-driven approach to COVID-19 infection forecast for Nigeria using negative binomial regression model (2021)
Book Chapter

COVID-19: the new wave of a global pandemic, is bringing about an increasing number of scientific efforts aimed at enabling governments to make informed decisions. In this paper, we explore the negative binomial regression model from the family of ge... Read More about Data-driven approach to COVID-19 infection forecast for Nigeria using negative binomial regression model.

Understanding unconventional preprocessors in deep convolutional neural networks for face identification (2019)
Journal Article

Deep convolutional neural networks have achieved huge successes in application domains like object and face recognition. The performance gain is attributed to different facets of the network architecture such as: depth of the convolutional layers, ac... Read More about Understanding unconventional preprocessors in deep convolutional neural networks for face identification.

Aesthetic surgery induced transformation face insensitive features: The medical and theoretical standpoint (2017)
Presentation / Conference Contribution

The changes in facial appearance resulting from the effect of plastic surgery may manifest in the form of textural variations, and/or geometric variations with respect to the facial structural features such as eyes, nose, mouth, jaw, nose, brow, etc.... Read More about Aesthetic surgery induced transformation face insensitive features: The medical and theoretical standpoint.

Minimizing separability: A comparative analysis of illumination compensation techniques in face recognition (2017)
Journal Article

Feature extraction task are primarily about making sense of the discriminative features/patterns of facial information and extracting them. However, most real world face images are almost always intertwined with imaging modality problems of which... Read More about Minimizing separability: A comparative analysis of illumination compensation techniques in face recognition.

Recognizing surgically altered faces using local edge gradient Gabor magnitude pattern (2017)
Presentation / Conference Contribution

For humans, every face is unique and can be recognized amongst similar faces. This is yet to be so for machines. Our assumption is that beneath the uncertain primitive visual features of face images are intrinsic structural patterns that uniquely dis... Read More about Recognizing surgically altered faces using local edge gradient Gabor magnitude pattern.

On gradient descriptor distribution-based dimensionality reduction analysis: A case of recognizing plastic surgery sample faces (2016)
Journal Article

Objectives: To analyze the influence of the sparseness distribution characteristics of gradient-based descriptor data on reduction of high-dimensional data, this paper presents experimental analysis on learned samples of gradient descriptor data. Met... Read More about On gradient descriptor distribution-based dimensionality reduction analysis: A case of recognizing plastic surgery sample faces.

Channel measurement and time dispersion analysis for outdoor mobile ultrawideband environment (2016)
Journal Article

Ultrawideband (UWB) technology offers short-range high-data transmission rates. Most researchers in recent times have focused on indoor UWB channel measurements and in instances where outdoor cases were reported, they focused on static scenarios. Thi... Read More about Channel measurement and time dispersion analysis for outdoor mobile ultrawideband environment.