English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

The clothing fashion reflects the common aesthetics that people share witheach other in dressing. To recognize the fashion time of a clothing ismeaningful for both an individual and the industry. In this paper, under theassumption that the clothing fashion changes year by year, the fashion-timerecognition problem is mapped into a clothing-fashion classification problem.Specifically, a novel deep neural network is proposed which achieves accuratehuman body segmentation by fusing multi-scale convolutional features in a fullyconvolutional network, and then feature learning and fashion classification areperformed on the segmented parts avoiding the influence of image background. Inthe experiments, 9,339 fashion images from 8 continuous years are collected forperformance evaluation. The results demonstrate the effectiveness of theproposed body segmentation and fashion classification methods.

Fusing Hierarchical Convolutional Features for Human Body Segmentation and Clothing Fashion Classification