Research outputs

JOURNAL ARTICLES

  • Almeida, A., De Villiers, J.P., De Freitas, A. & Velayudan, M. 2022. “The complementarity of a diverse range of deep learning features extracted from video content for video recommendation”. Expert Systems with Applications, Vol 192.
  • Beckedahl, D. & and Pillay, N. 2020. A study of bi-space search for solving the one-dimensional bin packing problem. 19th International Conference on Artificial Intelligence and Soft Computing, Lecture Notes in Artificial Intelligence, Vol. 12416, 277–289.
  • Beckedahl, D. & Pillay, N. 2022. Bi-space search: Optimising the hybridisation of search spaces in solving the one-dimensional bin packing problem, International Conference on Artificial Intelligence and Soft Computing, Lecture Notes in Artificial Intelligence, accepted.
  • Hassan, A. & Pillay, N. 2021. Dynamic heuristic set selection for cross-domain selection hyper-heuristics. Lecture Notes in Computer Science: Theory and Practice of Natural Computing, Tenth International Conference, December 2021, pp. 33–46.
  • Hassan, A. & Pillay, N. 2022. Automated design of dynamic heuristic set selection for cross-domain selection hyper-heuristics. International Conference on Artificial Intelligence and Soft Computing, Lecture Notes in Artificial Intelligence, accepted.
  • Singh, E. & Pillay, N. 2021. Ant-based generation constructive hyper-heuristics for the movie scene scheduling problem. Lecture Notes in Computer Science: Theory and Practice of Natural Computing, Tenth International Conference, December 2021, pp. 109–120.
  • Singh, E. & Pillay, N. 2021. Ant-based hyper-heuristics for the movie science scheduling problem. 20th International Conference on Artificial Intelligence and Soft Computing, Lecture Notes in Artificial Intelligence, pp. 342–353.
  • Singh, E. & Pillay, N. 2022. A study of ant-based pheromone spaces for generation constructive hyper-heuristics. Swarm and Evolutionary Computation. Vol 72, July 2022, 101095.

CONFERENCE PROCEEDINGS

  • Almeida, A., De Villiers, J.P., De Freitas, A. & Velayudan, M. 2020. Visual comparison of statistical feature aggregation methods for video-based similarity applications, 23rd International Conference on Information Fusion, Pretoria, South Africa, 6–9 July 2020, pp. 22–29.
  • Beckedahl, D., Nel, A. & Pillay, N. 2019. A study of multi-space search optimisation. International Conference on Intelligent Systems Design and Applications: Advances of Intelligent Systems and Computing, Vol. 940, Springer, pp. 1–9.
  • Gerber, M. & Pillay, N. 2022. Automated design of feature extraction for unsupervised image clustering using grammatical evolution, accepted for publication in the 2022 IEEE Symposium on Computational Intelligence, September.
  • Hassan, A. & Pillay, N. 2021. An investigation of automated design of VMAF. Proceedings of the 2021 IEEE Symposium Series on Computational Intelligence, pp. 1–8.
  • Hassan, A. & Pillay, N. 2022. Automated design of hybrid metaheuristics: Fitness landscape analysis. In proceedings of the IEEE World Congress for Computational Intelligence, accepted.
  • Hassan, A. & Pillay, N. 2022. Hybridising a genetic algorithm with reinforcement learning for automated design of genetic Algorithms. In proceedings of the IEEE World Congress for Computational Intelligence, accepted.
  • Mervitz, J., De Villiers, J.P., Jacobs, P. and Kloppers, M. 2020. Comparison of early and late fusion techniques for movie trailer genre labelling, 23rd International Conference on Information Fusion, Pretoria, South Africa, 6–9 July 2020, pp. 708–713.
  • Pretorius, K.W. & Pillay, N. 2020. A comparative study of classifiers for thumbnail selection. Proceedings of the 2020 IEEE International Joint Conference on Neural Networks.
  • Pretorius, K.W. & Pillay, N. 2021. Population-based reinforcement learning, Proceedings of the 2021 IEEE Symposium Series on Computational Intelligence, pp. 1–8.
  • Singh, E. & Pillay, N. 2022. A parameter-based analysis of ant-based generation hyper-heuristics, accepted for publication in the 2022 IEEE Symposium on Computational Intelligence, September. 
  • Singh, E. & Pillay, N. 2022. A study of transfer learning in an ant-based generation construction hyper-heuristic. In Proceedings of the IEEE World Congress for Computational Intelligence, accepted.

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