… by deep learning algorithms. This article starts with a brief introduction to digital holographic
… 10–12], deep learning can shorten the time in sample pre-processing, eliminate many steps …

… deep learning to develop real-time hologram generation. We propose an original concept of
introducing hologram … pre-processing mechanism to train a generative model to learn and …

… years, we employed deep learning a Convolutional Neural Net (… of genuine hologram types
(in our case Euro banknote holograms, … After fine-tuning, each hologram PHS was processed …

… to the capability of interconnection and light speed processing in parallel. The present unified
… These recent progresses suggest that the distinct fields of holography and deep learning …

… As such, the network automatically learns internal representations of the necessary processing
steps in holographic reconstruction and builds up a connection in pixel-level between a …

… Thus, by exploiting the real-time capture and processing capabilities and incorporating the
… incoherent holographic cameras, we propose a deep learning-based hologram filtering …

… propose a deep learning-based network for phase-only hologram … hologram-related
research, there have been attempts to apply a deep learning-based approach for post-processing …

… In this work, we propose a phase-only hologram compression and decompression scheme
incorporating both JPEG standard and deep learning post-processing. In this scheme, the …

… the graphic processing unit (GPU) and central processing units (… bits, and additional information
for data processing. The sum of this … Table 1 summarizes the specifications for hologram …

… pipeline to reconstruct one single QPM from the recorded digital hologram … , deep convolutional
neural networks (DCNNs) have been employed to speed up the holographic processing …