Matrix-based character design systems: Parallel principles in manga matrix and lora for neural networks - Anthoni Reza Pahlevi; Alvanov Zpalanzani Mansoor (Deskomvis: Jurnal Ilmiah Desain Komunikasi Visual, Seni Rupa dan Media, 2025)
The integration of AI in character design lacks systematic frameworks that translate traditional visual design principles into computational parameters, creating a conceptual gap between designers' artistic intent and AI tool configuration. This research identifies four parallel principles—structural decomposition, modular recombination, granular control, and hierarchical organization—shared between Hiroyoshi Tsukamoto's Manga Matrix and Low-Rank Adaptation (LoRA), developing the first translation framework that maps visual design decisions to specific LoRA parameters. We reveal how matrix-based organizational principles create actionable pathways for designer-AI collaboration, establishing that these systems share fundamental operational mechanisms despite their distinct domains. Through literature review and comparative analysis, we examine how Manga Matrix's visual grid elements correspond to LoRA's rank values and weight distributions, establishing practical implementation guidelines for each principle. The research establishes foundational methodology for human-AI co-creation, contributing to more practical and consistent AI-assisted design workflows.