1-2hit |
Fashen LI Jianrong SUN Xuewen WANG Jianbo WANG
Mn1-xZnxFe2O4 thin films with various Zn contents, 300 nm in thickness, were synthesized on glass substrates directly by electroless plating in aqueous solution at 90 without a heat treatment. With XRD, SEM, VSM, the crystallographic structure, morphology of the films and the macroscopic magnetic properties were characterized. The Mn-Zn ferrite films have a single phase spinel structure and well-crystallized columnar grains grow perpendicularly to the substrate. The change of the coercivity is not consistent with that of the bulk materials. As the Zn content in the films increases, the value of Hc decreases firstly, and then increases. At x=0.5, the minimum value of Hc is 3.7 kA/m and the value of Ms is 419.6 kA/m. The hyperfine magnetic fields, cation occupations and the distribution of the magnetic moments in film plane were studied by the conversion electron Mossbauer spectroscopy (CEMS).
Jianbo WANG Haozhi HUANG Li SHEN Xuan WANG Toshihiko YAMASAKI
The image-to-image translation aims to learn a mapping between the source and target domains. For improving visual quality, the majority of previous works adopt multi-stage techniques to refine coarse results in a progressive manner. In this work, we present a novel approach for generating plausible details by only introducing a group of intermediate supervisions without cascading multiple stages. Specifically, we propose a Laplacian Pyramid Transformation Generative Adversarial Network (LapTransGAN) to simultaneously transform components in different frequencies from the source domain to the target domain within only one stage. Hierarchical perceptual and gradient penalization are utilized for learning consistent semantic structures and details at each pyramid level. The proposed model is evaluated based on various metrics, including the similarity in feature maps, reconstruction quality, segmentation accuracy, similarity in details, and qualitative appearances. Our experiments show that LapTransGAN can achieve a much better quantitative performance than both the supervised pix2pix model and the unsupervised CycleGAN model. Comprehensive ablation experiments are conducted to study the contribution of each component.