AI RESEARCH
VTBench: A Multimodal Framework for Time-Series Classification with Chart-Based Representations
arXiv CS.LG
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ArXi:2604.27259v1 Announce Type: cross Time-series classification (TSC) has advanced significantly with deep learning, yet most models rely solely on raw numerical inputs, overlooking alternative representations. While texture-based encodings such as Gramian Angular Fields (GAF) and Recurrence Plots (RP) convert time series into 2D images, they often require heavy preprocessing and yield less intuitive representations.