User Interface Of System For Classification And Attribution Of Artwork For Authentication And Valuation

A system for analyzing an artwork, the system comprising:

• one or more processors, a display unit operably coupled to the one or more processors, and a memory accessible by the processor, the memory storing instructions that when executed by the processor implement a method comprising:
• displaying, via a graphical user interface (GUI), wherein the GUI includes an image capture option for receiving an image of an artwork from a user;
• pre-processing the received image to enhance image quality for analysis;
• analyzing, by a computer vision module, the pre-processed image to generate visual embeddings representing features of the artwork, wherein the computer vision module comprises a feature extraction unit configured to apply convolutional neural networks (CNNs) to detect low-level and high-level visual features including brushstrokes, textures, shapes, and color distributions, a generative analysis unit configured to employ generative adversarial networks (GANs) to distinguish between authentic and forged stylistic elements, a sequential analysis unit configured to employ recurrent neural networks (RNNs) or transformer-based models to identify temporal, stylistic, or contextual sequences across related artworks, and an embedding generation unit configured to transform the extracted features into numerical embeddings;
• combining, by an artificial intelligence engine comprising a multimodal fusion module, the visual embeddings with contextual data obtained from a metadata library comprising subject matter identifiers curated by subject matter experts and a statistical identifiers database comprising historical sales records and provenance data to generate feature representations;
• generating, by an authentication unit, an authentication output indicative of authenticity of the artwork;
• determining, by a valuation probability calculator, a valuation probability by applying a Bayesian network to integrate the feature representations, the authentication output, and contextual market data, the Bayesian network comprising nodes representing valuation factors and edges representing conditional dependencies among the valuation factors to generate the valuation probability indicating a probable change in valuation of the artwork;
• displaying, through the GUI on the display unit, graphical visualizations of the authentication output and the valuation probability corresponding to the artwork;
• and
• enabling user interaction with the GUI to view detailed information related to identified art identifiers and valuation probability.