mlsanityData to 14 Oct 2026

Classification of Time-Series Images Using Deep Convolutional Neural Networks

arXiv 1710.00886 ↗First posted 2 Oct 2017cs.CVcited by 38

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Abstract (arXiv)

Convolutional Neural Networks (CNN) has achieved a great success in image recognition task by automatically learning a hierarchical feature representation from raw data. While the majority of Time-Series Classification (TSC) literature is focused on 1D signals, this paper uses Recurrence Plots (RP) to transform time-series into 2D texture images and then take advantage of the deep CNN classifier. Image representation of time-series introduces different feature types that are not available for 1D signals, and therefore TSC can be treated as texture image recognition task. CNN model also allows learning different levels of representations together with a classifier, jointly and automatically. Therefore, using RP and CNN in a unified framework is expected to boost the recognition rate of TSC. Experimental results on the UCR time-series classification archive demonstrate competitive accuracy of the proposed approach, compared not only to the existing deep architectures, but also to the state-of-the art TSC algorithms.

Key facts. Cited by 38 papers in the map (data through 14 Oct 2026). First posted on arXiv 2 Oct 2017.

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Citing papers per year: 2021: 5; 2022: 4; 2023: 7; 2024: 6; 2025: 10; 2026: 6.

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  1. 2024VisionTS: Visual Masked Autoencoders Are Free-Lunch Zero-Shot Time Series Forecasterscited by 88
  2. 2023Time Series as Images: Vision Transformer for Irregularly Sampled Time Seriescited by 79
  3. 2023Deep Learning for Time Series Classification and Extrinsic Regression: A Current Surveycited by 68
  4. 2024Utilizing Image Transforms and Diffusion Models for Generative Modeling of Short and Long Time Seriescited by 43
  5. 2025Harnessing Vision Models for Time Series Analysis: A Surveycited by 26
  6. 2021A Novel CNN-LSTM-based Approach to Predict Urban Expansioncited by 13
  7. 2025VisionTS++: Cross-Modal Time Series Foundation Model with Continual Pre-trained Vision Backbonescited by 12
  8. 2024TimEHR: Image-based Time Series Generation for Electronic Health Recordscited by 8
  9. 2025A Diffusion Model for Regular Time Series Generation from Irregular Data with Completion and Maskingcited by 7
  10. 2021Fully Homomorphically Encrypted Deep Learning as a Servicecited by 6
  11. 2025AimTS: Augmented Series and Image Contrastive Learning for Time Series Classificationcited by 6
  12. 2024How Deep is your Guess? A Fresh Perspective on Deep Learning for Medical Time-Series Imputationcited by 5
26 more
  1. 2025Channel Selected Stratified Nested Cross Validation for Clinically Relevant EEG Based Parkinsons Disease Detectioncited by 5
  2. 2022Semi-supervised multiscale dual-encoding method for faulty traffic data detectioncited by 3
  3. 2023MCI Detection using fMRI time series embeddings of Recurrence plotscited by 3
  4. 2022Spectral Propagation Graph Network for Few-shot Time Series Classificationcited by 2
  5. 2022Investigating Temporal Convolutional Neural Networks for Satellite Image Time Series Classification: A surveycited by 2
  6. 2024Sensor-Aware Classifiers for Energy-Efficient Time Series Applications on IoT Devicescited by 2
  7. 2025Towards Measuring and Modeling Geometric Structures in Time Series Forecasting via Image Modalitycited by 2
  8. 2021A Novel Multi-Stage Training Approach for Human Activity Recognition from Multimodal Wearable Sensor Data Using Deep Neural Networkcited by 1
  9. 2021Image Classifiers for Network Intrusionscited by 1
  10. 2022Pre-Trained Language Transformers are Universal Image Classifierscited by 1
  11. 2023Automated Cardiovascular Record Retrieval by Multimodal Learning between Electrocardiogram and Clinical Reportcited by 1
  12. 2024Multi-step feature fusion for natural disaster damage assessment on satellite imagescited by 1
  13. 2025Integrating Sequence and Image Modeling in Irregular Medical Time Series Through Self-Supervised Learningcited by 1
  14. 2025Moon: A Modality Conversion-based Efficient Multivariate Time Series Anomaly Detectioncited by 1
  15. 2026VTBench: A Multimodal Framework for Time-Series Classification with Chart-Based Representationscited by 1
  16. 2021Deep Neural Networks on EEG Signals to Predict Auditory Attention Score Using Gramian Angular Difference Fieldcited by 0
  17. 2023A Dynamic Temporal Self-attention Graph Convolutional Network for Traffic Predictioncited by 0
  18. 2023Image Transformation for IoT Time-Series Data: A Reviewcited by 0
  19. 2023Fast Classification of Large Time Series Datasetscited by 0
  20. 2025Vision4PPG: Emergent PPG Analysis Capability of Vision Foundation Models for Vital Signs like Blood Pressurecited by 0
  21. 2025Temporal-Visual Semantic Alignment: A Unified Architecture for Transferring Spatial Priors from Vision Models to Zero-Shot Temporal Taskscited by 0
  22. 2026A Framework for Feature Discovery in Intracranial Pressure Monitoring Data Using Neural Network Attentioncited by 0
  23. 2026Hyperspectral Trajectory Image for Multi-Month Trajectory Anomaly Detectioncited by 0
  24. 2026GAFSV-Net: A Vision Framework for Online Signature Verificationcited by 0
  25. 2026Naturalness Predicts but Does Not Cause Transferability in Image Encodings of Real-World Streamscited by 0
  26. 2026VEIL: How Visual Encoding Hijacking Induces Bias In Vision Modelscited by 0