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page: 2 type: comment created: 2020-02-19T20:47:29.061Z

--- page: 1 type: text-highlight created: 2020-02-19T21:20:29.067Z color: #9900EF artistic rendering, --- page: 1 type: text-highlight created: 2020-02-19T21:20:39.725Z color: #9900EF mage processing --- page: 1 type: text-highlight created: 2020-02-20T19:47:04.344Z color: #9900EF Image-based Artistic Rendering --- page: 1 type: text-highlight created: 2020-02-20T19:47:25.421Z color: #9900EF neural style transfer (NST) --- page: 1 type: text-highlight created: 2020-02-20T19:47:29.859Z color: #9900EF Computing methodologies --- page: 1 type: text-highlight created: 2020-02-20T19:48:00.279Z color: green propose a semiotic structure to derive a technical research agenda for NSTs with respect to the grand challenges of NPAR. --- page: 1 type: text-highlight created: 2020-02-20T19:48:15.357Z color: #FF6900 it also has to evolve as an interactive tool that considers the design aspects and mecha- nisms of artwork production --- page: 3 type: text-highlight created: 2020-02-21T00:34:02.932Z color: yellow Semiotics deals with the study of symbols and how they communi- cate image contents or information in a meaningful way [Bertin 2010] --- page: 3 type: text-highlight created: 2020-02-21T00:34:12.443Z color: green SEMIOTIC STRUCTURE FOR ARTISTIC STYLE TRANSFER --- page: 2 type: text-highlight created: 2020-02-21T00:35:02.082Z color: #9900EF ARTISTIC STYLE TRANSFER --- page: 3 type: text-highlight created: 2020-02-21T00:37:42.200Z color: #8ED1FC Denition “Artistic Style”: --- page: 4 type: text-highlight created: 2020-02-21T00:41:41.537Z color: #FF6900 NST techniques apparently lack to model graphical ele- ments/variables and provide interactive (creative) control --- type: area-highlight created: 2020-02-21T00:42:38.462Z color: image: file:///C:/Users/jeang/.polar/files/image/12ASqusSBoV2HZmTgUVy.png --- page: 3 type: text-highlight created: 2020-02-21T01:55:03.048Z color: #FF6900 a semiotic structure that considers these design aspects and the mechanisms of interactive NPAR has not been formulated yet. --- page: 3 type: text-highlight created: 2020-02-21T01:55:52.089Z color: green evolve (neural) style transfers as interactive tools that ease the visual expression of artists, non-artists and scientists for illus- trative visualization [Gooch et al. 2010; Isenberg 2016; Salesin 2002] --- page: 4 type: text-highlight created: 2020-02-21T01:56:54.701Z color: yellow Modeling Aspects --- page: 4 type: text-highlight created: 2020-02-21T01:57:02.675Z color: yellow Filtering Aspects --- page: 4 type: text-highlight created: 2020-02-21T01:59:32.342Z color: #9900EF semiology principles of Bertin [2010] and MacEachren et al. [2012] that provide a theoretical foundation to visualization (Figure 4). --- page: 6 type: text-highlight created: 2020-02-26T21:04:57.687Z color: yellow Style Transfer using Neural Networks --- page: 3 type: text-highlight created: 2020-02-28T04:18:21.600Z color: yellow Style Transfer using Image Analogies : Techniques that use image pairs for training—a source image and an artistic depiction of this image—i. e., to learn an analogous transfor- mation such that content images can be transformed into an artistic rendering of similar visual style [Hertzmann et al. 2001]. --- page: 3 type: text-highlight created: 2020-02-28T04:18:27.419Z color: yellow Style Transfer using Neural Networks: Techniques that employ neural networks to separate and recombine the content and style of arbitrary inputs. Typically, loss func- tions are minimized iteratively to balance the components of style and content in the output [Gatys et al. 2016b], or train feed-forward neural networks for linear image trans- formation [Johnson et al. 2016a,b]. --- page: 3 type: text-highlight created: 2020-02-28T04:19:56.185Z color: #F78DA7 (1) Heuristics-based Algorithms: Paradigms that are based on rendering functions, which are implemented by a do- main expert who explicitly models individual artistic styles and its correspondent design aspects or mechanisms. This group basically comprises stroke-based rendering, region- based techniques, image processing and ltering, and may also account for physically-based simulations. --- page: 3 type: text-highlight created: 2020-02-28T04:20:15.171Z color: #F78DA7 (2) Style Transfer Algorithms : Example-based rendering which is directed to learn or reproduce artistic styles from visual examples (ground-truth data sets). This type often comprises statistical models and optimization schemes to balance aspects of content and style in the stylized output --- type: area-highlight created: 2020-02-28T04:20:47.471Z color: image: file:///C:/Users/jeang/.polar/files/image/12pG7CqCPbKiAPaPBzBQ.png --- type: area-highlight created: 2020-02-28T19:31:12.561Z color: image: file:///C:/Users/jeang/.polar/files/image/1x4uKapcsnzsh99rhSDA.png --- page: 6 type: text-highlight created: 2020-02-28T21:57:57.406Z color: green Feed-forward Approaches --- page: 3 type: text-highlight created: 2020-02-28T23:48:06.845Z color: yellow Denition “Artistic Style”: The constant form—and some- times the constant elements, qualities, and expression—in the art of an individual or a group. — Meyer Schapiro [Schapiro 1994] --- page: 1 type: text-highlight created: 2020-06-16T19:25:42.844Z color: yellow Semmo