- author = "Julio J. Valdes and Zachary Baird and Sreeraman Rajan and Miodrag Bolic",
- title = "Radar-based Noncontact Human Activity Classification Using Genetic Programming",
- booktitle = "2020 IEEE Congress on Evolutionary Computation, CEC 2020",
- year = "2020",
- editor = "Yaochu Jin",
- pages = "paper id24140",
- address = "internet",
- month = "19-24 " # jul,
- organization = "IEEE Computational Intelligence Society",
- publisher = "IEEE Press",
- keywords = "genetic algorithms, genetic programming",
- isbn13 = "978-1-7281-6929-3",
-
DOI = "
doi:10.1109/CEC48606.2020.9185814",
- abstract = "This paper analyses the structure of the feature space of radar data collected from real subjects either still or in motion and provides dimensionality reduction and modeling through genetic programming. Three movement classes: sedentary and still, sedentary with movements, and walking contained in the returns obtained from a single channel continuous wave phase-modulated radar are considered. Unsupervised methods are used for finding the intrinsic dimensionality of the space of the original features and nonlinear mappings are used to obtain lower dimensional representations. The classification results for the original and the reduced dimension data are similar, thus, indicating the redundancy of the eliminated features. The white-box models obtained through genetic programming is then compared with the conventional black-box models obtained through supervised classification using random trees, extreme learning machines and multilayer perceptron. For this problem, the explicit white-box models obtained with genetic programming produced equal or better classification accuracies than those obtained with black-box approaches. In addition to explainability, the genetic programming models found have the additional advantage of involving only a few relevant predictors, exhibiting good feature selection capabilities.",
-
notes = "https://wcci2020.org/
Digital Technologies Research Centre, National Research Council Canada, Ottawa, Canada; Department of Systems and Computer Engineering, Carleton University, Ottawa, Canada; School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, Canada.
Also known as \cite{9185814}",
