TINTO vs REFINED vs IGTD: Comparing Tabular-to-Image Methods in TINTOlib
Comparative analysis of TINTO, REFINED and IGTD, three representative tabular data into synthetic image transformation methods ...
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Blog & Tutorials
Blog & Tutorials
Technical tutorials, research notes and reproducible examples on TINTOlib, tabular-to-image transformation, synthetic image generation from tabular data, hybrid neural networks, explainable AI and applied deep learning.
By Manuel Castillo-Cara, PhD — Researcher and Professor at UNED, developer of TINTO and TINTOlib.
Improving Deep Learning by Exploiting Synthetic Images — Part II: From Synthetic Images to Hybrid Neural Networks
Part II of a theoretical and technical series on synthetic images for tabular data, focusing on TINTOlib, preferred spatial enc...
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Improving Deep Learning by Exploiting Synthetic Images — Part I: Why Tabular Data Needs Spatial Representations
Part I of a theoretical and technical series on why deep learning still struggles with tabular data, and why synthetic image re...
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What is TINTOlib and why should we transform tabular data into synthetic images?
An introduction to TINTOlib: why tabular data requires spatial encoding, how to generate synthetic images avoiding data leakage...
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Introduction to TINTOlib: Unlocking the Power of Vision Architectures for Tabular Data
Technical introduction to TINTOlib, a Python framework for transforming tabular data into synthetic images and applying CNN-bas...
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