A Neural-Network-Based Watermarking Method Approximating JPEG Quantization.

We propose a neural-network-based watermarking method that introduces the quantized activation function that approximates the quantization of JPEG compression. Many neural-network-based watermarking methods have been proposed. Conventional methods have acquired robustness against various attacks by introducing an attack simulation layer between the embedding network and the extraction network. The quantization process of JPEG compression is replaced by the noise addition process in the attack layer of conventional methods. In this paper, we propose a quantized activation function that can simulate the JPEG quantization standard as it is in order to improve the robustness against the JPEG compression. Our quantized activation function consists of several hyperbolic tangent functions and is applied as an activation function for neural networks. Our network was introduced in the attack layer of ReDMark proposed by Ahmadi et al. to compare it with their method. That is, the embedding and extraction networks had the same structure. We compared the usual JPEG compressed images and the images applying the quantized activation function. The results showed that a network with quantized activation functions can approximate JPEG compression with high accuracy. We also compared the bit error rate (BER) of estimated watermarks generated by our network with those generated by ReDMark. We found that our network was able to produce estimated watermarks with lower BERs than those of ReDMark. Therefore, our network outperformed the conventional method with respect to image quality and BER.

Synergy Effect of Plasmonic Field Enhancement and Light Confinement in Mesoporous Titania-Coated Aluminum Nanovoid Photoelectrode.

Photoelectrochemical (PEC) water splitting is a highly demanded technology for the realization of sustainable society. Various types of photoanodes have been developed to achieve high efficiency of PEC water splitting. Plasmonic field enhancement and light confinement effects are often adopted to improve PEC performance. However, their synergistic effects have not been studied. In this work, a mesoporous TiO2 layer was deposited on an Al plate with a nanovoid array structure, which acts as a photoanode and simultaneously exhibits a light confinement effect and surface plasmon resonance. The solo and synergy effects were investigated through experimental photocurrent measurements and theoretical simulations using the finite-difference time-domain method. The highest improvement in PEC performance was confirmed when the synergy effect occurred.