Ensemble Convolutional Neural Network for Classifying Holograms of Deformable Objects

Recently, a method known as “ensemble deep learning invariant hologram classification” (EDL-IHC) for classifying holograms of deformable objects with deep learning network has been demonstrated. Similar to classifiers in general DL-IHC cannot attain 100% success rates. However, it is always desirable to have a success rate that is closer to perfection in practice. In this paper we propose an enhanced method known as “ensemble deep learning invariant hologram classification” (EDL-IHC). In comparison with DL-IHC, our proposed hologram classifier has promoted the success rate by over 2.85% in the classification of holograms of handwritten numerals.