Elijah Omidiora

Ladoke Akintola University of Technology · Department of Computer Science and Engineering

A hybrid learning system (HLS) is a technique of combining traditional face-to-face teaching with the online teaching method. It is otherwise known as a blended learning system (BLS). It is an e-learning technique that relies on a web app and ensures effective teaching and learning between the instructors and students, some HLS applications also co...

Iris recognition is considered as one of the best biometric methods used for human identification and verification because of its unique features that differ from one person to another. Self-Organizing Feature Map (SOFM) and Back Propagation Neural Network (BPNN) are two techniques that have been used previously for iris recognition but their perfo...

Following the rapid growth of cities,the continuous expansion of cities, too many vehicles competing for limited capacity transportation, Researchers on a daily basis are working tirelessly to solve the problem of road traffic congestion as it increases the increasing probability of accidents and has a negative impact on the environment. In this pa...

Activation functions are an extremely important part of the artificial neural networks that are used to calculate weighted and biases and also to generate the outputs of neural network. However, selecting an appropriate activation transfer for a classification problem has been task faced by researchers. This paper presented an approach for evaluati...

Age estimation is the ability to predict the age of an individual based on facial clues. This could be put to practical use in underage voting detection, underage driving detection, and overage sportsmen detection. To date, no popular automatic age estimation system has been developed to target black faces. This study developed a novel age estimati...

Classification is a crucial stage in identification systems, most specifically in biometric identification systems. A weak and inaccurate classification system may produce false identity, which in turn impacts negatively on delicate decisions. Decision making in biometric systems is done at the classification stage. Due to the importance of this st...

A computer-based age estimation is a technique that predicts an individual's age based on visual traits derived by analyzing a 2D picture of the individual's face. Age estimation is critical for access control, e-government, and effective human–computer interaction. The other-race effect has the potential to cause techniques designed for white face...

Unimodal biometrics system (UBS) drawbacks include noisy data, intra-class variance, inter-class similarities, non-universality, which all affect the system's classification performance. Intramodal fingerprint fusion can overcome the limitations imposed by UBS when features are fused at the feature level as it is a good approach to boost the perfor...

E-commerce theft involves using lost/stolen debit/credit cards, forging checks, misleading accounting practices, etc. Due to carelessness of cardholders and criminality activities of fraudsters, the personal identification number (PIN) and using account level based fraud detection techniques methods are inadequate to cub the activities of fraudster...

Grammar-checking is a concept of interest in many natural language environments. It typically involves the evaluation of the grammaticality of transmitted messages, be it written or verbal. Automated grammaticality evaluation is the examination of natural language text for grammatical accuracy using computer software. The current study examined dif...

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Digital Industrial Control Systems (ICS) are complex electromechanical systems composed of components such as sensors, actuators, programmable logic controllers and communication devices interconnected to perform monitoring and control tasks in different industries. ICS have many and varied applications in critical infrastructures across the globe....

The concept of automated grammar evaluation of natural language texts is one that has attracted significant interests in the natural language processing community. It is the examination of natural language text for grammatical accuracy using computer software. The current work is a comparative study of different deep and shallow parsing techniques...

Several criminal profiling systems have been developed to assist the Law Enforcement Agencies in solving crimes but the techniques employed in most of the systems lack the ability to cluster criminal based on their behavioral characteristics. This paper reviewed different clustering techniques used in criminal profiling and then selects one fuzzy c...

Restaurant industry has become one of the most profitable industries in the world where incessant long waiting time may not only lead to customers’ dissatisfactions but also facilitate loosing of customers to other competitors. In this paper, in order to determine customers’ arrival patterns and service patterns which are critical factors in determ...

Despite significant research efforts for School Timetabling Problem (STP) and other timetabling problems, an effective solution approach (model and algorithm) which provides boundless use and high quality solution has not been developed. Hence, this paper presents a novel solution approach for solving school timetabling problem which characterizes...

School timetabling is an important operational problem in many high schools. It is a classical combinatorial optimization problem, proved to be NP-hard. For this reason, extensive research has been carried out on automated high school timetabling in the past 59 years. This research ranges from theoretical investigations and surveysto case studies i...

School timetabling is an important operational problem in many high schools. It is a classical combinatorial optimization problem, proved to be NP-hard. For this reason, extensive research has been carried out on automated high school timetabling in the past 59 years. This research ranges from theoretical investigations and surveysto case studies...

Due to an ever-growing need to automatically authenticate individuals, biometrics remained an active field of research over the course of the last decade. Biometric has been proved to be a reliable means of enforcing constraint in a security sensitive environment. Identifying the people through their ear is the emerging trend in the modern era. Hum...

Due to an ever-growing need to automatically authenticate individuals, biometrics remained an active field of research over the course of the last decade. Biometric has been proved to be a reliable means of enforcing constraint in a security sensitive environment. Identifying the people through their ear is the emerging trend in the modern era. Hum...

Objective: to experiment the performance of optimization of hybridized counter propagation neural network (CPNN) with genetic algorithm (GA) to detect anomaly in credit cards online transactions. Methods: One thousand three hundred transactional data from thirteen cardholders were simulated which contained a mix of genuine and fraudulent transactio...

One of the most reliable biometrics when issues of access control and security is been considered is face recognition. An integral part of a face recognition system is the feature extraction stage, which becomes a critical problem where is a need to obtain the best feature with minimum classification error and low running time. Many of the existing...

This is a 5th series Faculty Lecture presentation of the Faculty of Engineering and Technology of the Ladoke Akintola University of Technology, Ogbomoso, Oyo State, Nigeria. The lecture took place on the 18th June 2019, based on the topic: PATTERN RECOGNITION: A ROADMAP TOWARDS NATIONAL PLANNING AND DEVELOPMENT

During Nigerian 2015 general elections, in an attempt to exercise their civic rights in voting for the candidates of their choices, many electorates exercised the limitations of their patience by tiredly waiting on queue for their turn at the poll centers. In order to study the aforementioned scenario, this paper carried out a simulation based anal...

Measuring the complexity of software has been an insoluble problem in software engineering. Complexity measures can be used to predict critical information about testability of software system from automatic analysis of the source code. In this paper, Improved Cognitive Complexity Metric (ICCM) is applied on C programming language. Since C is a pro...

Aim: To develop a Curvelet Transform (CT)-Local Binary Pattern (LBP) feature extraction technique for mass detection and classification in digital mammograms. Study Design: A feature extraction technique. Place and Duration of Study: Sample: Department of Computer Science and Engineering LAUTECH, Ogbomoso, Nigeria 2016. Methodology: Three hundred (...

Significant investments are being made yearly to improve service quality and delivery in banking systems to minimise customers' dissatisfactions with long waiting time due to overcrowding. However, most existing empirical studies to address this problem employed the method where the system was modelled and then developed a program that will simulat...

This paper presents a comparison between Iterative Back Projection (IBP) and Discrete Algebraic Reconstruction Technique (DART). In this experiment, images were acquired using a digital camera of 5Mega Pixel (MP). A total of 50 images were used. The Images were degraded by introducing noise, blur and shift in angle. DART and IBP were used to recons...

Significant investments are being made yearly to improve service quality and delivery in banking systems to minimise customers' dissatisfactions with long waiting time due to overcrowding. However, most existing empirical studies to address this problem employed the method where the system was modelled and then developed a program that will simulat...

Many face recognition algorithms perform poorly in real life surveillance scenarios because they were tested with datasets that are already biased with high quality images and certain ethnic or racial types. In this paper a black face surveillance camera (BFSC) database was described, which was collected from four low quality cameras and a professi...

Handwriting recognition is one of the most fascinating and challenging research areas in the field of image processing and pattern recognition which emanates from the need for humans to automate the recognition of handwritten text and enable the computer to receive and interpret them. Several handwritten character recognition systems had been devel...

There exist several natural language processing systems that focus on checking the grammaticality (grammatical correctness or incorrectness) of natural language texts. Studies however showed that most existing systems do not assign specific scores to the grammaticality of the analysed text. Such scores would for instance prove very useful to second...

Large variation in facial appearances of the same individual makes most baseline Aging-Invariant Face Recognition Systems (AI-FRS) suffer from high automatic misclassification of faces. However, some Aging-Invariant Feature Extraction Techniques (AI-FET) for AI-FRS are emerging to help achieve good recognition results when compared to some baseline...

Authors' contributions This work was carried out in collaboration between all authors. Author ATT reviewed the existing works feature extraction techniques (texture based, shape based and intensity based). Author ATM reviewed different works of mass features (descriptors) used by different authors, feature extraction approaches and feature selectio...

This study investigates the relative efficacy of using n-grams extracted terms, the aggregation of such terms, and a combination of feature extraction techniques in building an automated essay-type grading (AETG) system. The paper focused on the modification of the Principal Component Analysis (PCA) by integrating n-grams terms as input into the PC...

Mobile agent is a software object that migrates through many nodes of a heterogeneous network of computers under its own control in order to perform task using resources of these nodes, during the past several years, mobile agent has received significant attention. Not only in the wide range of commercial and law enforcement applications, but also...

Human faces undergo considerable amount of variations with aging. This variation being experienced in facial texture and shape with different ages of a particular subject makes recognition of faces very difficult. However, most existing Face Recognition Systems (FRS) suffer from high misclassification of faces because of the large variation in face...

Efficient e-learners activities model is essential for real time identifications and adaptive responses. Determining the most effective Neuro-Fuzzy model amidst plethora of techniques for structure and parameter identifications is a challenge. This paper illustrates the implication of system identification techniques on the performance of Adaptive...

_______________________________________________________________________________ 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...

Age estimation from facial features is an important research subject in the field of face recognition. It is an active research area that can be used in wide range of applications such as surveillance and security, telecommunication and digital libraries, human-computer intelligent interaction, and smart environment. This paper developed an unsuper...

Instructional design (ID) models are proven prescriptive techniques for qualitative lessons that could guarantee learning. Existing Learning Management Systems (LMS) miss-out the roles of this important quality control mechanism by providing a mere plane and passive platform for content authoring, thus becomes vulnerable for poor instructional desi...

This paper presents a typewritten characters recognition system using Hidden Markov Model (HMM). Character recognition systems convert images of printed, typewritten or handwritten documents into computer readable texts that can be easily edited or searched. Character recognition for typewritten documents is however difficult due to broken edges, t...

Aim: This paper presents a statistical analysis of the performance of two age estimation algorithms namely Back Propagation Neural Network (BPNN) and Self Organizing Feature Map (SOFM) on human face images. Methodology: 630 human face images with age ranges 0 - 69 from the FG-NET database were considered, feature extraction was done using Principal...

A mobile agent is a software entity that migrates from one host to another, performing data collection and software configuration tasks on behalf of users in distributed networks. However, studies have shown that the existing pull – all data strategy of mobile agent migration pattern moves data from one host to the next host along with the mobile a...

This paper presents a recognition system for Yorùbá handwritten words using Hidden Markov Model(HMM).The work is divided into four stages, namely data acquisition, preprocessing, feature extraction and classification. Data were collected from adult indigenous writers and the scanned images were subjected to some level of preprocessing, such as: gre...

Age estimation is the determination of a person’s age based on biometric features such as face, finger print etc. it is a hard problem for both humans and the computer system. In this paper, back propagation neural network was used to classify face images into eight different age groups ranging from babies, young teenagers, mid teenagers, teenagers...

Online character recognition is characterized with feature extraction and classification parameters that make recognition accuracy non-trivial task. Failure of existing optimization techniques to yield an acceptable solution to solve poor feature selection and slow convergence time provokes the idea for some stochastic algorithms. In this paper, a...

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...

Face recognition has been an active research area in the pattern recognition and computer vision domains due to its many potential applications in surveillance, credit cards, passport and security. However, the problem of correct method of partitioning the face data into train and test set has always been a challenge to the development of a robust...

Face emotion recognition systems identify emotions expressed on the face without necessarily identifying the person involved, as in Face recognition. Support Vector Machine (SVM) has been shown to give better performance on other classification tasks but has not been applied to emotion recognition, especially with still face images. This research w...

Many face recognition algorithms perform poorly in real life surveillance scenarios because they were tested with datasets that are already biased with high quality images and certain ethnic or racial types. In this paper a black face surveillance camera (BFSC) database was described, which was collected from four low quality cameras and a professi...

Classification is the process of assigning a class to a group of objects. Moving objects classification can be difficult a task in the presence of dynamic factors like occlusion clutters and shadows. This paper developed a classifier for moving images (video stream) by using a modified adaptive background mixture model method. This system removes s...