AI RESEARCH
Semimage: HSV-Based Semantic Image Encoding for Disentangled Text Representation
arXiv CS.LG
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ArXi:2512.00088v2 Announce Type: replace-cross We propose SemImage, a novel method for representing a text document as a two-dimensional semantic image to be processed by convolutional neural networks (CNNs). In a SemImage, each word is represented as a pixel in a 2D image: rows correspond to sentences and an additional boundary row is inserted between sentences to mark semantic transitions.