Conference Information

ICCPR 2026: International Conference on Computing and Pattern Recognition

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Submission Date:
2026-06-20 Extended
Notification Date:
2026-07-10
Conference Date:
2026-10-29
Location:
Wuxi, China
Years:
15
Viewed: 32287   Tracked: 44   Attend: 8

Conference Partner Index (CP-I)

52.9 / 100
Ranked #1,019 of 5,651 conferences · Top 19%

#39 of 241 in Computer Vision & Pattern Recognition

Academic recognition (35%) No data - scored at the neutral baseline of 50 —
Submission selectivity (20%) No data - scored at the neutral baseline of 50 —
Editions held (20%)
75
Community attention (10%)
52
Public record completeness (15%)
35

Inputs used: Editions on record: 15 · Researchers following it here: 44 · Researchers who opened this page in the past 24 months: 7

Missing from the public record: Historical acceptance rates (+4.5) · Past editions (+3.0) · Best-paper records (+2.3)
Organizers can add these from this page after claiming the conference; scores are recomputed nightly. How to raise this score

Confidence 45% - the share of the score backed by observed data rather than the neutral baseline. How this score is calculated · Browse the ranking · Algorithm version 1.1 · Computed 2026-09-07

Call For Papers

ICCPR 2026 (International Conference on Computing and Pattern Recognition) is an academic conference held in Wuxi, China on 2026-10-29. The paper submission deadline is 2026-06-20 (extended). Acceptance notifications are sent on 2026-07-10.

Topics of interest include, but are not limited to: Track I Computer Vision and Image Processing Image segmentation and annotation Object detection and recognition Image generation and synthesis Video analysis and action recognition Image quality assessment and enhancement Track II Pattern Recognition and Data Mining Pattern classification and clustering Feature selection and dimensionality reduction Anomaly detection and outlier analysis Applications of pattern recognition in biomedicine and healthcare Data mining and knowledge discovery Track III Machine Learning and Deep Learning Machine learning algorithms and methods Deep learning models and architectures Reinforcement learning and transfer learning Feature extraction and representation learning Reinforcement learning and adaptive learning Track IV Natural Language Processing and Text Analysis Language models and semantic representation Machine translation and cross-lingual processing Text classification and sentiment analysis Named entity recognition and relation extraction Text generation and summarization Track V Human-Computer Interaction and Intelligent Systems Multimodal interaction and affective computing Virtual reality and augmented reality Intelligent recommendation and personalized services Human-Computer collaboration and intelligent assistants Autonomous driving and intelligent transportation Track VI Data Analysis and Big Data Data preprocessing and cleansing Large-scale data analysis and processing Data visualization and interaction Data privacy and security Data analysis in cloud computing environment Track VII Face Recognition and Biometrics Face detection and recognition Biometric identification and authentication Contactless biometric recognition technologies Multimodal biometric systems Facial expression analysis and emotion recognition Track VIII Time Series Analysis and Forecasting Time series modeling and analysis Time series forecasting and trend analysis Event detection and anomaly detection High-dimensional time series analysis Time series data mining and applications Track IX Reinforcement Learning and Adaptive Control Model-based reinforcement learning Model-free reinforcement learning Multi-agent reinforcement learning Adaptive control and optimization Deep reinforcement learning and real-world applications Track X Media Analysis and Content Understanding Video content analysis and understanding Audio signal processing and music analysis Image and video retrieval Media understanding and semantic analysis Social media analysis and mining
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