Opeyemi Lateef Usman

448 total citations
16 papers, 304 citations indexed

About

Opeyemi Lateef Usman is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering. According to data from OpenAlex, Opeyemi Lateef Usman has authored 16 papers receiving a total of 304 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 6 papers in Computer Vision and Pattern Recognition and 4 papers in Electrical and Electronic Engineering. Recurrent topics in Opeyemi Lateef Usman's work include Stock Market Forecasting Methods (3 papers), Brain Tumor Detection and Classification (3 papers) and Energy Load and Power Forecasting (3 papers). Opeyemi Lateef Usman is often cited by papers focused on Stock Market Forecasting Methods (3 papers), Brain Tumor Detection and Classification (3 papers) and Energy Load and Power Forecasting (3 papers). Opeyemi Lateef Usman collaborates with scholars based in Malaysia, Nigeria and Iran. Opeyemi Lateef Usman's co-authors include Ravie Chandren Muniyandi, Mazlyfarina Mohamad, Khairuddin Omar, Shahnorbanun Sahran, Suziyani Mohamed, Rogayah A. Razak and Olusegun Folorunso and has published in prestigious journals such as PLoS ONE, Scientific Reports and IEEE Access.

In The Last Decade

Opeyemi Lateef Usman

15 papers receiving 278 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Opeyemi Lateef Usman Malaysia 7 130 71 40 34 33 16 304
Mohammad Wedyan Jordan 12 59 0.5× 86 1.2× 56 1.4× 21 0.6× 63 1.9× 36 323
Ruixin Ma China 7 145 1.1× 104 1.5× 38 0.9× 3 0.1× 36 1.1× 34 338
Ke Niu China 8 71 0.5× 79 1.1× 45 1.1× 4 0.1× 62 1.9× 31 258
Onur Cezmi Mutlu United States 7 48 0.4× 124 1.7× 52 1.3× 5 0.1× 68 2.1× 20 325
Harald Burgsteiner Austria 9 48 0.4× 125 1.8× 45 1.1× 30 0.9× 25 0.8× 17 346
Cristina Nader Vasconcelos Brazil 9 40 0.3× 90 1.3× 115 2.9× 17 0.5× 15 0.5× 27 323
Milan Gnjatović Serbia 9 38 0.3× 103 1.5× 46 1.1× 7 0.2× 33 1.0× 32 246
Carlos M. Fernandes Portugal 10 69 0.5× 96 1.4× 23 0.6× 7 0.2× 16 0.5× 22 268
Aseel Alhadlaq Saudi Arabia 6 23 0.2× 86 1.2× 37 0.9× 7 0.2× 31 0.9× 9 260

Countries citing papers authored by Opeyemi Lateef Usman

Since Specialization
Citations

This map shows the geographic impact of Opeyemi Lateef Usman's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Opeyemi Lateef Usman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Opeyemi Lateef Usman more than expected).

Fields of papers citing papers by Opeyemi Lateef Usman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Opeyemi Lateef Usman. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Opeyemi Lateef Usman. The network helps show where Opeyemi Lateef Usman may publish in the future.

Co-authorship network of co-authors of Opeyemi Lateef Usman

This figure shows the co-authorship network connecting the top 25 collaborators of Opeyemi Lateef Usman. A scholar is included among the top collaborators of Opeyemi Lateef Usman based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Opeyemi Lateef Usman. Opeyemi Lateef Usman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

16 of 16 papers shown
1.
2.
Muniyandi, Ravie Chandren, et al.. (2024). Restoring private autism dataset from sanitized database using an optimized key produced from enhanced combined PSO-GWO framework. Scientific Reports. 14(1). 15763–15763. 1 indexed citations
3.
Usman, Opeyemi Lateef, et al.. (2023). Efficient Neuroimaging Data Security and Encryption Using Pixel-Based Homomorphic Residue Number System. SN Computer Science. 4(6). 2 indexed citations
4.
Muniyandi, Ravie Chandren, et al.. (2022). A Hybrid Method of Enhancing Accuracy of Facial Recognition System Using Gabor Filter and Stacked Sparse Autoencoders Deep Neural Network. Applied Sciences. 12(21). 11052–11052. 6 indexed citations
5.
Usman, Opeyemi Lateef, Ravie Chandren Muniyandi, Khairuddin Omar, & Mazlyfarina Mohamad. (2022). Privacy-Preserving Classification Method for Neural-Biomarkers using Homomorphic Residue Number System CNN: HoRNS-CNN. 1–8. 4 indexed citations
6.
Muniyandi, Ravie Chandren, et al.. (2022). Impact of Cloud-Based Customer Relationship Management (CRM) in Healthcare Sector. 1–7. 2 indexed citations
7.
Usman, Opeyemi Lateef, et al.. (2022). The Rise of Ransomware: A Review of Attacks, Detection Techniques, and Future Challenges. 1–7. 17 indexed citations
8.
Usman, Opeyemi Lateef, Ravie Chandren Muniyandi, Khairuddin Omar, & Mazlyfarina Mohamad. (2021). Advance Machine Learning Methods for Dyslexia Biomarker Detection: A Review of Implementation Details and Challenges. IEEE Access. 9. 36879–36897. 62 indexed citations
9.
Usman, Opeyemi Lateef, Ravie Chandren Muniyandi, Khairuddin Omar, & Mazlyfarina Mohamad. (2021). Gaussian smoothing and modified histogram normalization methods to improve neural-biomarker interpretations for dyslexia classification mechanism. PLoS ONE. 16(2). e0245579–e0245579. 24 indexed citations
10.
Muniyandi, Ravie Chandren, et al.. (2021). Artificial neural network with Taguchi method for robust classification model to improve classification accuracy of breast cancer. PeerJ Computer Science. 7. e344–e344. 38 indexed citations
11.
Usman, Opeyemi Lateef & Ravie Chandren Muniyandi. (2020). CryptoDL: Predicting Dyslexia Biomarkers from Encrypted Neuroimaging Dataset Using Energy-Efficient Residue Number System and Deep Convolutional Neural Network. Symmetry. 12(5). 836–836. 21 indexed citations
12.
Usman, Opeyemi Lateef, et al.. (2020). A Review of Machine Learning Methods of Feature Selection and Classification for Autism Spectrum Disorder. Brain Sciences. 10(12). 949–949. 115 indexed citations
13.
14.
Folorunso, Olusegun, et al.. (2016). PREDICTING STUDENTS«¤?? ENROLLMENT USING GENERALIZED FEED-FORWARD NEURAL NETWORK. 14(1). 61–73. 2 indexed citations
15.
Folorunso, Olusegun, et al.. (2016). PREDICTING STUDENTS«¤?? GRADE SCORES USING TRAINING FUNCTIONS OF ARTIFICIAL NEURAL NETWORK. 14(1). 27–45. 6 indexed citations
16.
Usman, Opeyemi Lateef, et al.. (2014). Predicting Electricity Consumption Using Radial Basis Function (RBF) Network. 4(2). 54–63. 3 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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2026