• Examination of customized questioned digital documents 

  Adedayo, Oluwasola Mary; Olivier, Martin S. (Wiley, 2025-03)

  With the increasing trend of digitization of business processes and personal communication across the globe, digital documents of intrinsic value continue to be created. Whereas the questioned document examination (QDE) ...
• Multi-objective evolutionary neural architecture search for recurrent neural networks 

  Booysen, Reinhard; Bosman, Anna (Springer, 2024-06-18)

  Artificial neural network (NN) architecture design is a nontrivial and time-consuming task that often requires a high level of human expertise. Neural architecture search (NAS) serves to automate the design of NN ...
• Data fingerprinting and visualization for AI-enhanced cyber-defence systems 

  Klopper, Christiaan; Eloff, Jan H.P. (Institute of Electrical and Electronics Engineers, 2024-10)

  Artificial intelligence (AI)-assisted cyber-attacks have evolved to become increasingly successful in every aspect of the cyber-defence life cycle. For example, in the reconnaissance phase, AI-enhanced tools such as MalGAN ...
• Fine-tuning retrieval-augmented generation with an auto-regressive language model for sentiment analysis in financial reviews 

  Mathebula, Miehleketo; Modupe, Abiodun; Marivate, Vukosi (MDPI, 2024-12)

  Sentiment analysis is a well-known task that has been used to analyse customer feedback reviews and media headlines to detect the sentimental personality or polarisation of a given text. With the growth of social media ...
• Training feedforward neural networks with Bayesian hyper-heuristics 

  Schreuder, Arné; Bosman, Anna Sergeevna; Engelbrecht, Andries P.; Cleghorn, Christopher W. (Elsevier, 2025-01)

  The process of training feedforward neural networks (FFNNs) can benefit from an automated process where the best heuristic to train the network is sought out automatically by means of a high-level probabilistic-based ...
• ChatGPT as a text annotation tool to evaluate sentiment analysis on South African financial institutions 

  Mathebula, Miehleketo; Modupe, Abiodun; Marivate, Vukosi (Institute of Electrical and Electronics Engineers, 2024-09)

  Social media platforms play a significant role in analyzing customer perceptions of financial products and services in today’s culture. These platforms facilitate the immediate and in-depth sharing of thoughts and ...
• On the transparency of large AI models 

  Wang, Wanying; Wang, Ge; Marivate, Vukosi; Hufton, Andrew L. (Cell Press, 2023-07)

  As large AI models demonstrate increasingly human-like performance on complex tasks, many scientists are developing or adapting these models to empower their research and applications. Because of the substantial costs ...
• Denoising diffusion post-processing for low-light image enhancement 

  Panagiotou, Savvas; Bosman, Anna (Elsevier, 2024-12)

  Low-light image enhancement (LLIE) techniques attempt to increase the visibility of images captured in low-light scenarios. However, as a result of enhancement, a variety of image degradations such as noise and color bias ...
• Using distributed ledger technology for digital forensic investigation purposes on tendering projects 

  Ramazhamba, T.P.; Venter, H.S. (Hein) (Springer, 2023-03-09)

  The South African Local Government (SALG) uses the tendering system to procure goods and services. Some of these tendering projects are aimed at promoting socio-economic and industrial policies. Hence, the tendering system ...
• Exploring COVID-19 public perceptions in South Africa through sentiment analysis and topic modelling of Twitter posts 

  Kekere, Temitope; Marivate, Vukosi; Hattingh, Maria J. (Marie) (Learning Information Networking and Knowledge (LINK) Centre, Graduate School of Public and Development, 2023)

  The narratives shared on social media during a health crisis such as COVID-19 reflect public perceptions of the crisis. This article provides findings from a study of the perceptions of South African citizens regarding ...
• Neural network crossover in genetic algorithms using genetic programming 

  Pretorius, Kyle; Pillay, Nelishia (Springer, 2024-06)

  The use of genetic algorithms (GAs) to evolve neural network (NN) weights has risen in popularity in recent years, particularly when used together with gradient descent as a mutation operator. However, crossover operators ...
• A genetic programming approach to the automated design of CNN models for image classification and video shorts creation 

  Kapoor, Rahul; Pillay, Nelishia (Springer, 2024-03)

  Neural architecture search (NAS) is a rapidly growing field which focuses on the automated design of neural network architectures. Genetic algorithms (GAs) have been predominantly used for evolving neural network architectures. ...
• Combating hate : how multilingual transformers can help detect topical hate speech 

  Srikissoon, Trishanta; Marivate, Vukosi (Easychair, 2023)

  Automated hate speech detection is important to protecting people’s dignity, online experiences, and physical safety in Society 5.0. Transformers are sophisticated pre-trained language models that can be fine-tuned for ...
• Regularised feed forward neural networks for streamed data classification problems 

  Ellis, Mathys; Bosman, Anna Sergeevna; Engelbrecht, Andries P. (Elsevier, 2024-07)

  Streamed data classification problems (SDCPs) require classifiers to not just find the optimal decision boundaries that describe the relationships within a data stream, but also to adapt to changes in the decision boundaries ...
• Application of deep reinforcement learning in asset liability management 

  Wekwete, Takura Asael; Kufakunesu, Rodwell; Van Zyl, A.J. (Gusti) (Elsevier, 2023-11)

  Asset Liability Management (ALM) is an essential risk management technique in Quantitative Finance and Actuarial Science. It aims to maximise a risk-taker’s ability to fulfil future liabilities. ALM is especially critical in ...
• Technology-enhanced learning, data sharing, and machine learning challenges in South African education 

  Combrink, Herkulaas MvE; Marivate, Vukosi; Masikisiki, Baphumelele (MDPI, 2023-04-24)

  The objective of this paper was to scope the challenges associated with data-sharing governance for machine learning applications in education research (MLER) within the South African context. Machine learning applications ...
• A multi-population particle swarm optimization-based time series predictive technique 

  Kuranga, Cry; Muwani, Tendai S.; Ranganai, Njodzi (Elsevier, 2023-12)

  In several businesses, forecasting is needed to predict expenses, future revenue, and profit margin. As such, accurate forecasting is pivotal to the success of those businesses. Due to the effects of different exogenous ...
• MalFe—malware feature engineering generation platform 

  Singh, Avinash; Ikuesan, Richard Adeyemi; Venter, H.S. (Hein) (MDPI, 2023-10-08)

  The growing sophistication of malware has resulted in diverse challenges, especially among security researchers who are expected to develop mechanisms to thwart these malicious attacks. While security researchers have ...
• A review and comparative study of cancer detection using machine learning : SBERT and SimCSE application 

  Mokoatle, Mpho; Marivate, Vukosi; Mapiye, Darlington; Bornman, Maria S. (Riana); Hayes, Vanessa M. (BMC, 2023-03-23)

  BACKGROUND : Using visual, biological, and electronic health records data as the sole input source, pretrained convolutional neural networks and conventional machine learning methods have been heavily employed for the ...
• Machine learning approaches identify chemical features for stage-specific antimalarial compounds 

  Van Heerden, Ashleigh; Turon, Gemma; Duran-Frigola, Miquel; Pillay, Nelishia; Birkholtz, Lyn-Marie (American Chemical Society, 2023-11-07)

  Efficacy data from diverse chemical libraries, screened against the various stages of the malaria parasite Plasmodium falciparum, including asexual blood stage (ABS) parasites and transmissible gametocytes, serve as a ...

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