scholarly journals Development of Web-Based Participatory Trend Forecasting System: urtrend.net

2011 ◽  
pp. 65-73
Author(s):  
Eui-Chul Jung ◽  
SoonJong Lee ◽  
HeeYun Chung ◽  
BoSup Kim ◽  
HyangEun Lee ◽  
...  
Keyword(s):  
Web Based ◽  
Trend Forecasting ◽  
Forecasting System

A Web-based flood forecasting system for Shuangpai region

2006 ◽  
Vol 37 (3) ◽  
pp. 146-158 ◽  
Author(s):  
Xiang-Yang Li ◽  
K.W. Chau ◽  
Chun-Tian Cheng ◽  
Y.S. Li
Keyword(s):  
Flood Forecasting ◽  
Web Based ◽  
Forecasting System

scholarly journals Web-based forecasting system for the airborne spread of livestock infectious disease using computational fluid dynamics

2015 ◽  
Vol 129 ◽  
pp. 169-184 ◽  
Author(s):  
Il-hwan Seo ◽  
In-bok Lee ◽  
Se-woon Hong ◽  
Hyun-seok Noh ◽  
Joo-hyun Park
Keyword(s):  
Infectious Disease ◽  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Web Based ◽  
Forecasting System

Neo-Fashion: A Data-Driven Fashion Trend Forecasting System Using Catwalk Analysis

2021 ◽  
pp. 0887302X2110042
Author(s):  
Li Zhao ◽  
Muzhen Li ◽  
Peng Sun
Keyword(s):  
Trend Analysis ◽  
Diffusion Of Innovation ◽  
Training Data ◽  
Data Driven ◽  
Fashion Industry ◽  
Diffusion Of Innovation Theory ◽  
Trend Forecasting ◽  
Forecasting System ◽  
Analysis System ◽  
The Given

Trend forecasting is a challenging and important aspect of the fashion industry. The authors design a novel fashion trend analysis system called “Neo-Fashion,” which provides recommendations to fashion researchers and practitioners about potential fashion trends using computer vision and machine learning. Neo-Fashion includes three modules, a data collection and labeling module, an instance segmentation module and a trend analysis module. Diffusion of innovation theory is used as the main theoretical framework to understand fashion trends. 32,702 catwalk images from 2019 fashion week were collected, and 769 images were labeled as training data. Neo-fashion is able to identify and segment fashion items in the given images, and indicate the fashion trends in colors, styles, clothing combinations, and other fashion attributes. To optimize the system, more data sources can be included to not only reflect trends in even more categories but also aid in understanding the trickle-up or trickle-across process in fashion.

scholarly journals Research on Trend Forecasting System Utilizing Big Data Network and Information Technology

2021 ◽  
Vol 1982 (1) ◽  
pp. 012148
Author(s):  
An Xing ◽  
Shi Yan ◽  
Zang Yang ◽  
Lu Yan ◽  
Ren Yue
Keyword(s):  
Information Technology ◽  
Big Data ◽  
Data Network ◽  
Trend Forecasting ◽  
Forecasting System
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