A curated list of paper, methods and libraries implemented in Python for transforming tabular data into images.
- IGTD - Image Generator for Tabular Data (IGTD) is an algorithm for transforming tabular data into images.
- REFINED - Representation of Features as Images with NEighborhood Dependencies to create images from tabular data.
- DeepInsight - DeepInsight: A methodology to transform a non-image data to an image for convolution neural network architecture.
- tab2vox - Tab2vox neural architecture search (NAS) model as a method to convert a high-dimensional tabular sample into a well-formed 3D voxel image
- DAFT - DAFT: A Universal Module to Interweave Tabular Data and 3D Images in CNNs.
- Vec2image - Vec2image: an explainable artificial intelligence model for the feature representation and classification of high-dimensional biological data by vector-to-image conversion.
- DCNNTr - DCNNTr
- IP3G - IP3G
- Wrangling - Wrangling
- Fotomics - Fotomics
- IGTD - Image Generator for Tabular Data (IGTD) is an algorithm for transforming tabular data into images.
- REFINED - Representation of Features as Images with NEighborhood Dependencies to create images from tabular data.
- DeepInsight - DeepInsight: A methodology to transform a non-image data to an image for convolution neural network architecture.
- tab2vox - Tab2vox neural architecture search (NAS) model as a method to convert a high-dimensional tabular sample into a well-formed 3D voxel image
- DAFT - DAFT: A Universal Module to Interweave Tabular Data and 3D Images in CNNs.
- Vec2image - Vec2image: an explainable artificial intelligence model for the feature representation and classification of high-dimensional biological data by vector-to-image conversion.
- IP3G - IP3G:
- Wrangling - Wrangling
- Fotomics - Fotomics
- Neural Networks for NLP - Carnegie Mellon Language Technology Institute there
MIT