Olusayo Deborah Fenwa

• PhD
• Professor (Full) at Ladoke Akintola University of Technology

Multimodal biometric systems have garnered significant interest from researchers owing to their applicability in security and access control. Despite the development of numerous score level fusion techniques for multimodal biometrics, most of them have concentrated solely on enhancing fusion accuracy, neglecting the potential advantages of various...

Access control systems are crucial for securing sensitive data and system components by allowing authorized access while blocking unauthorized entities. Traditional unimodal biometric systems, make use of a single physiological or behavioral trait, have limitations such as susceptibility to spoofing and environmental constraints, leading to reduced...

Due to the advancement in the Internet of Things (IoT) devices, the different sectors have greatly expanded through connectivity and flexibility. However, these various devices and networks present certain difficulties for the digital forensic investigations, especially, in the aspects of the devices type variety and data integrity. In later years...

Securing medical images on the internet, in public or local networks is very important because they contain sensitive information about the well-being of patients and help health personnel to carry out diagnoses easily. Data Encryption Standard (DES) has been a popular algorithm used for image encryption due to its low memory consumption and good t...

The developments in science and technology have made it possible to use biometrics in applications where it is required to establish or confirm the identity of individuals. Among all possible biometric characteristics, the use of iris texture for recognition of individuals has been proven to be highly reliable. However, existing iris prediction sys...

Aims: To evaluate the performance of an Improved Latent Semantic Analysis (ILSA), Latent Semantic Analysis (LSA), Non-Negative Matrix Factorization (NMF) algorithms in an Electronic Assessment Application using metrics, Term Similarity, Precision, Recall and F-measure functions, Mean divergence, Assessment Accuracy and Adequacy in Semantic Represen...

The fraud associated with credit card transaction is increasing at an alarming rate and consequently resulting in huge financial loss for both the cardholders and concerned financial institutions. Most datasets for real-life problems such as this are usually imbalanced, which makes the machine learning model not robust for training purposes. Theref...

Diabetic Retinopathy (DR) is a medical condition where the retina is damaged because fluid leaks from blood vessels into the retina. Ophthalmologists recognize diabetic retinopathy based on features, such as blood vessel area, exudes, hemorrhages, microaneurysms and texture. Aim: The focus of this paper is to evaluate the performance of Decision Tr...

Face recognition is considered to be one of the most reliable biometrics where security issues are of concerned. Feature extraction which is a functional block of a face recognition system becomes a critical problem when there is need to obtain the best feature with minimum classification error and low running time. Most existing face recognition s...

In recent years, deep learning techniques have already been impacting wide range of information processing, pattern recognition, image processing and computer vision related works within the traditional and widened scopes. Hence, this research explored a generative deep architecture approach to better engage soft and hard biometric features for ide...

This paper carries out performance evaluation of a Modified Genetic Algorithm (MGA) and Modified Counter Propagation Network (MCPN) Network for online character recognition. Two techniques were used to train the feature vectors using supervised and unsupervised methods. First, the modified genetic algorithm used feature selection to filter irreleva...

Very large collections of images are growing ever more common. From stock photo collections to proprietary databases to the Web, these collections are diverse and often poorly indexed; unfortunately, image retrieval systems have not kept pace with the collections they are searching. The shortcomings of these systems are due both to the image repres...

In today's society, advances in technology have made life easier by providing us with higher levels of knowledge through the invention of different devices. However, each technological innovation harbours the potential of hidden threats to its users. One major threat is theft of private or personal data, information and properties. As digital data...

_______________________________________________________________________________ Abstract Feature extraction and feature selection place an important role in online character recognition and as procedure in choosing the relevant feature that yields minimum classification error. Character recognition has been a good research area for many years becau...

In today's society, advances in technology have made life easier by providing us with higher levels of knowledge through the invention of different devices. However, each technological innovation harbours the potential of hidden threats to its users. One major threat is theft of private or personal data, information and properties. As digital data...

Facial expressions remain a significant component of human-to-human interface and have the potential to play a correspondingly essential part in human-computer interaction. Support Vector Machine (SVM) by the virtue of its application in a various domain such as bioinformatics, pattern recognition, and other nonlinear problems has a very good gener...

Accurate diagnosis of cancer plays an important role in order to save human life. The results of the diagnosis indicate by the medical experts are mostly differentiated based on the experience of different medical experts. This problem could risk the life of the cancer patients. A fast and effective method to detect the lung nodules and separate th...

ABSTRACT Character Recognition has become an intensive research areas during the last few decades because of its potential applications. However, most existing classifiers used in recognizing handwritten online characters suffer from poor feature selection and slow convergence which affect training time and recognition accuracy. This paper proposed...

Character Recognition has been one of the most intensive research during the last few decades because of its potential applications. However, most existing classifiers used in recognizing online handwritten characters suffer from poor feature selection and slow convergence which affect training time and recognition accuracy. Hence, this paper focus...

Character Recognition has been one of the most intensive research during the last few decades because of its potential applications. However, most existing classifiers used in recognizing online handwritten characters suffer from poor feature selection and slow convergence which affect training time and recognition accuracy. Hence, this paper focus...

Character Recognition has been one of the most intensive research during the last few decades because of its potential applications. However, most existing classifiers used in recognizing online handwritten characters suffer from poor feature selection and slow convergence which affect training time and recognition accuracy. Hence, this paper focus...

Character Recognition has become an intensive research areas during the last few decades because of its potential applications. However, most existing classifiers used in recognizing handwritten online characters suffer from poor feature selection and slow convergence which affect training time and recognition accuracy. This paper proposed a method...

INTRODUCTION The erythrocytes are the most numerous blood cells in the human body, and it also called red blood cells. The red blood cell functions as a carrier of oxygen throughout our body. [1] The normal red blood cell in our body is divided into four categories of ages, which are newborn, children, women and men. The average amount of red blood...

Medical image classification scheme has been on the increase in order to help physicians, and medical practitioners in their evaluation and analysis of diseases. Several classification schemes such as Artificial Neural Network (ANN), Bayes Classification, Support Vector Machine (SVM), K-Means Nearest Neighbor have been used. In this paper, we evalu...

Recognition of handwritten characters has become a difficult problem because of the high variability and ambiguity in the character shapes written by individuals. One of the major problems encountered by researchers in developing character recognition system is selection of efficient features (optimal features), low recognition accuracy and high re...

Traveling Salesman Problem (TSP) is a well-known, popular and extensively studied problem in the field of combinatorial optimization and attracts computer scientists, mathematicians and others. Its statement is deceptively simple, but yet it remains one of the most challenging problems in operational research. It also an optimization problem of fin...

Handwritten character recognition has applications in several industries such as Banking for reading of cheques and Libraries/ National archives for digital searchable storage of historic texts. The main feature typically used for the recognition task is the character image. However, there are other possible features such as the hand (left or right...

Automated recognition of handwritten digits has applications in several industries such as Postal and Banking for reading of addressed packages and cheques respectively. This paper compares four machine learning classifiers namely Naive Bayes, Instance Based Learner, Decision Tree and Neural Network for single digit recognition. Our experiments wer...

An approximate numerical solution for the unsteady free convective flow of Sisko fluid with radiative heat transfer past a flat plate moving through a binary mixture has been obtained by solving the governing equations using numerical technique. Using a similarity variable, the governing non-linear partial differential equations have been transform...

Artificial neural networks are one of the widely used automated techniques. Though they yield high accuracy, most of the neural networks are computationally heavy due to their iterative nature. Hence, there is a significant requirement for a neural classifier which is computationally efficient and highly accurate. To this effect, a modified Counter...

Feeding in poultry farming in most developing countries like Nigeria is still manually carried out as high level of human involvement is required. This places an exorbitant cost of production on the farmer and reduces the expected return of investment. Besides, human intervention to poultry feeding is limited to fatigue, negligence, unfavorable wea...

Modern day technology has come with many problems of authentication. For instance, in E-Business transactions where potential buyers and sellers do not meet physically, it might be difficult to verify the identity of the people involved. In academic environment too, much more problems are evolving daily some of which are impersonations, fake regist...