摘要：Design intelligence,namely,artificial intelligence to solve creative problems and produce creative ideas,has improved rapidly with the new generation artificial ***,existing methods are more skillful in learning from data and have limitations in creating original ideas different from the training *** offers a promising method to produce creative designs by combining human inspiration and machines' computational *** propose a crowdsourcing intelligent design method called ‘flexible crowdsourcing design'.Design ideas produced through crowdsourcing design can be unreliable and inconsistent because they rely solely on selection among participants' submissions of *** contrast,the flexible crowdsourcing design method employs a cultivation procedure that integrates the ideas from crowd participants and cultivates these ideas to improve design quality at the same *** introduce a series of studies to show how flexible crowdsourcing design can produce original design ideas ***,we will describe the typical procedure of flexible crowdsourcing design,the refined crowdsourcing tasks,the factors that affect the idea development process,the method for calculating idea development potential,and two applications of the flexible crowdsourcing design ***,it summarizes the design capabilities enabled by crowdsourcing intelligent *** method enhances the performance of crowdsourcing design and supports the development of design intelligence.

摘要：Images are widely used by companies to advertise their products and promote awareness of their *** automatic synthesis of advertising images is challenging because the advertising message must be clearly conveyed while complying with the style required for the product,brand,or target *** this study,we proposed a data-driven method to capture individual design attributes and the relationships between elements in advertising images with the aim of automatically synthesizing the input of elements into an advertising image according to a specified *** achieve this multi-format advertisement design,we created a dataset containing 13280 advertising images with rich annotations that encompassed the outlines and colors of the elements,in addition to the classes and goals of the *** our probabilistic models,users guided the style of synthesized advertisements via additional constraints(e.g.,context-based keywords).We applied our method to a variety of design tasks,and the results were evaluated in several perceptual studies,which showed that our method improved users’satisfaction by 7.1%compared to designs generated by nonprofessional students,and that more users preferred the coloring results of our designs to those generated by the color harmony model and Colormind.