1. SMART TRAFFIC CONTROL SYSTEM USING YOLO-MODEL
Background of the study
Traffic congestion is a major problem in many cities, and the fixed-cycle light signal controllers are not resolving the high waiting time in the intersection. We see often a policeman managing the movements instead of the traffi...
2. DEVELOPMENT OF A DEEP LEARNING BASED VEHICLE LICENSE PLATE DETECTION SCHEME
ABSTRACT
This research developed a license plate and classification scheme using deep learning architecture which utilized transfer learning using pre-trained Convolutional Neural Network (CNN). The developed scheme used images obtained from Caltech dataset, Peking University VehicleID...
3. Predicting High Stress Regions in a Microstructure using Convolutional Neural Networks
Abstract
Origins of failure are often driven by localizations in material response due to the applied stress/strain state. These stress “hot spots” intuitively represent regions that accumulate higher damage than their surroundings, serving as prime locations for crack nucle...
4. The Impact of Artificial Intelligence Tools in Medical Imaging and Disease Prediction: A Case Study of General Hospital, Nasarawa State.
1.1 Background of the Study
Artificial Intelligence (AI) has emerged as a transformative force in healthcare, particularly in medical imaging and disease prediction. By leveraging machine learning algorithms and deep neural networks, AI systems can analyze complex medical data, enabling...
5. Design and Implementation of a Genomic Data Annotation System Using Deep Learning: A Case Study of Gombe State University, Gombe State
Background of the Study
The rapid expansion of genomic sequencing technologies has resulted in an exponential increase in raw genomic data. However, transforming these vast datasets into meaningful biological insights remains a critical challenge. Genomic data annotation&...
6. Design and Implementation of an AI‐Based Platform for Predicting Genetic Mutations: A Case Study of Bauchi State University, Gadau, Bauchi State
Background of the Study
The rapid advancements in genomic technologies have led to an exponential increase in genetic data, creating both opportunities and challenges in mutation prediction. Predicting genetic mutations accurately is critical for early diagnosis, personal...
7. Development of an AI-Powered Bioinformatics Tool for Predicting Drug Resistance in Tuberculosis: A Case Study of University of Maiduguri, Borno State
Background of the Study
Tuberculosis (TB) remains a significant global health threat, particularly in regions with high disease burden and emerging drug resistance. Rapid and accurate prediction of drug resistance is crucial for effective TB management and treatment. At U...
8. Evaluation of AI-Based Approaches for Analyzing Genomic Variants: A Case Study of Adamawa State University, Mubi, Adamawa State
Background of the Study
Genomic variants, including single nucleotide polymorphisms (SNPs) and insertions/deletions (indels), are critical in determining individual susceptibility to diseases and drug responses. At Adamawa State University, Mubi, researchers are evaluatin...
9. Development of an AI-Powered Bioinformatics Tool for Predicting Drug Resistance in Tuberculosis: A Case Study of University of Maiduguri, Borno State
Background of the Study
Tuberculosis (TB) remains a significant public health challenge, exacerbated by the emergence of drug-resistant strains. Rapid identification of drug resistance is essential for effective TB management. At University of Maiduguri, Borno State, rese...
10. Development of a Machine Learning-Based System for Identifying Mutations in Sickle Cell Disease: A Case Study of Federal University, Lokoja, Kogi State
Background of the Study
Sickle cell disease (SCD) is a hereditary blood disorder resulting from mutations in the hemoglobin gene, leading to significant morbidity and mortality. Early detection of pathogenic mutations is essential for effective disease management. At Fede...
11. Evaluation of the Use of Artificial Neural Networks in Predicting Disease Susceptibility: A Case Study of Federal University, Lafia, Nasarawa State
Background of the Study
Artificial Neural Networks (ANNs) have emerged as a potent subset of machine learning, capable of modeling complex, non-linear relationships in high-dimensional data. In the context of genetic research, ANNs offer significant advantages for predict...
12. Enhancing Genomic Variant Analysis Using AI-Driven Bioinformatics Approaches: A Case Study of Federal University, Kashere, Gombe State
Background of the Study
Genomic variant analysis is critical for understanding disease mechanisms and enabling precision medicine. However, the complexity of genomic data, including the vast number of variants and their intricate relationships, presents significant challe...
13. Implementation of a Deep Learning Framework for Studying Epigenomic Data: A Case Study of Nigerian Defence Academy, Kaduna State
Background of the Study
Epigenomics, which studies heritable changes in gene function without alterations in DNA sequence, is pivotal in understanding complex diseases such as cancer and neurological disorders. Deep learning, a subset of artificial intelligence, has the p...
14. Evaluation of the Use of Artificial Neural Networks in Predicting Disease Susceptibility: A Case Study of Federal University, Lafia, Nasarawa State
Background of the Study
Artificial Neural Networks (ANNs) have emerged as powerful tools for modeling complex, non-linear relationships in high-dimensional biological data. In genetic research, ANNs offer the potential to predict disease susceptibility by integrating geno...
15. Enhancing Genomic Variant Analysis Using AI-Driven Bioinformatics Approaches: A Case Study of Federal University, Kashere, Gombe State
Background of the Study
Genomic variant analysis is pivotal in understanding disease mechanisms, yet the complexity and sheer volume of sequencing data often hinder accurate variant detection. AI-driven bioinformatics approaches have the potential to revolutionize variant...
16. Implementation of a Deep Learning Framework for Studying Epigenomic Data: A Case Study of Nigerian Defence Academy, Kaduna State
Background of the Study
Epigenomic modifications play a critical role in regulating gene expression and are implicated in various diseases, including cancer and neurological disorders. Deep learning offers advanced analytical capabilities to decipher complex epigenomic pa...
17. Enhancing Genome Annotation Accuracy Using AI-Powered Bioinformatics Tools: A Case Study of Taraba State University, Jalingo, Taraba State
Background of the Study
Genome annotation, the process of identifying and labeling functional elements within a genome, is crucial for understanding the genetic blueprint of organisms (Zhang et al., 2023). Traditional annotation methods, while foundational, often strugg...
18. Enhancing Genomic Variant Prioritization Using Deep Learning Approaches: A Case Study of Ahmadu Bello University, Zaria, Kaduna State
Background of the Study :
Genomic variant prioritization is a critical step in identifying clinically significant mutations that may drive disease processes. With the rapid accumulation of genomic data, traditional methods of variant analysis are becoming increasingly inef...
19. Enhancing DNA Sequence Alignment Techniques Using Machine Learning Algorithms: A Case Study of Modibbo Adama University, Yola, Adamawa State
Background of the Study :
DNA sequence alignment is a critical step in genomic analysis, serving as the foundation for variant detection, phylogenetic studies, and functional annotation. Traditional alignment algorithms, while effective, often struggle with the increasing...
20. Implementation of AI‑Based Algorithms for Detecting Student Cheating in Online Exams in Federal University Wukari, Taraba State
Background of the Study
The rapid expansion of online examinations has been accompanied by rising concerns about academic integrity. In response, Federal University Wukari is investigating AI‑based algorithms that detect cheating in real time during online exams. With rem...
