Conference Information

PRML 2026: International Conference on Pattern Recognition and Machine Learning

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Submission Date:
2026-05-15 Extended
Notification Date:
2026-05-30
Conference Date:
2026-07-10
Location:
Urumqi, China
Years:
7
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Call For Papers

PRML 2026 (International Conference on Pattern Recognition and Machine Learning) is an academic conference held in Urumqi, China on 2026-07-10. The paper submission deadline is 2026-05-15 (extended). Acceptance notifications are sent on 2026-05-30.

PRML is an annual conference which aims to present the latest research and results of scholars and experts related to Pattern Recognition and Machine Learning. Topics of interest for submission include, but are not limited to: Track 1: Computer Vision and Recognition ◇ Image and Video Classification ◇ Object Detection and Tracking ◇ Semantic Segmentation ◇ Content-based Image Retrieval ◇ Facial Recognition ◇ 3D Reconstructions ◇ Action Recognition Track 2: Deep Learning and Optimization ◇ Neural Generative Models, Autoencoders, GANs ◇ Optimization and Learning Methods ◇ Representation Learning and Deep Learning ◇ Scene Analysis and Understanding ◇ Transfer Learning, Low-Shot, Semi- and Unsupervised Learning ◇ Motion and Tracking Track 3: Artificial Intelligence (AI) in Biomedical Applications ◇ AI in Biomedical Signal and Image Processing ◇ Bioinformatics for Healthcare Engineering ◇ Explainable AI, Fairness, Accountability, Privacy, Transparency and Ethics in Vision ◇ Biomedical Image Retrieval, Segmentation, Grouping and Shape using AI ◇ Applying Machine Learning-empowered Sensing to Biomedical Scenarios ◇ Distributed Computing for Big Data in Smart Healthcare using AI ◇ AI-enabled Remote Patient Monitoring using Big Data Track 4: Vision Applications and Systems ◇ Segmentation, Grouping, and Shape ◇ Vision + Language, Vision + Other Modalities ◇ Video Analysis and Understanding ◇ Vision Applications and Systems ◇ Vision for Robotics and Autonomous Vehicles ◇ Visual Reasoning and Logical Representation Track 5: Artificial Intelligence (AI) for Data Analytics ◇ Data Clustering, Classification, and Visualisation ◇ Explainable AI and Knowledge Discovery from Databases ◇ Fintech, Business Intelligence, Marketing Analytics, Risk Analytics and Decision Support ◇ Medical Diagnosis and Prognosis, Biomedical and Healthcare Analytics ◇ Predictive Maintenance, Condition Monitoring, Manufacturing Analytics ◇ Data Mining in Education, Transportation, Telecommunication, Agriculture, Energy, etc.
Last updated by Dunn Carl in

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