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@TECHREPORT{Penedones_Idiap-RR-30-2012,
         author = {Penedones, Hugo and Collobert, Ronan and Fleuret, Francois and Grangier, David},
       projects = {Idiap, IM2, MASH},
          month = {11},
          title = {Improving Object Classification using Pose Information},
           type = {Idiap-RR},
         number = {Idiap-RR-30-2012},
           year = {2012},
    institution = {Idiap},
       abstract = {We propose a method that exploits pose information in order to improve object classification. 
A lot of research has focused in other strategies, such as engineering feature extractors, trying different classifiers and even using transfer learning. Here, we use neural network architectures in a multi-task setup, whose outputs predict both the class and the camera azimuth. We investigate both Multi-layer Perceptrons and Convolutional Neural Network architectures, and achieve state-of-the-art results in the challenging NORB dataset.},
            pdf = {https://publications.idiap.ch/attachments/reports/2011/Penedones_Idiap-RR-30-2012.pdf}
}