Incremental learning for bootstrapping object classifier models

  title={Incremental learning for bootstrapping object classifier models},
  author={Cem Karaoguz and Alexander R. T. Gepperth},
  journal={2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC)},
Many state of the art object classification applications require many data samples, whose collection is usually a very costly process. Performing initial model training with synthetic samples (from virtual reality tools) has been proposed as a possible solution, although the resulting classification models need to be adapted (fine-tuned) to real-world data afterwards. For this bootstrapping process, we propose to use an incremental learning algorithm from the cognitive robotics domain which is… CONTINUE READING