Conference Information

S+SSPR 2026: IAPR Joint International Workshops on Statistical Techniques in Pattern Recognition and Structural and Syntactic Pattern Recongnition

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Submission Date:
2026-05-25 Extended
Notification Date:
2026-06-30
Conference Date:
2026-08-24
Location:
Bern, Switzerland
Years:
ICORE: B   QUALIS: B1   Viewed: 15402   Tracked: 2   Attend: 2
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S+SSPR
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Conference Partner Index (CP-I)

64.3 / 100
Ranked #463 of 5,694 conferences · Top 9%

#2 of 69 in Mathematics & Physical Sciences #15 of 246 in Computer Vision & Pattern Recognition

Academic recognition (35%)
78
Submission selectivity (20%) No data - scored at the neutral baseline of 50 —
Editions held (20%)
83
Community attention (10%)
21
Public record completeness (15%)
55

Inputs used: Listed as ICORE B, QUALIS B1 · Editions on record: 21 · Researchers following it here: 2 · Researchers who opened this page in the past 24 months: 3

Missing from the public record: Historical acceptance rates (+4.5) · 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 80% - 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 2026-10-09

Call For Papers

S+SSPR 2026 (IAPR Joint International Workshops on Statistical Techniques in Pattern Recognition and Structural and Syntactic Pattern Recongnition) is a ICORE B / QUALIS B1 conference held in Bern, Switzerland on 2026-08-24. The paper submission deadline is 2026-05-25 (extended). Acceptance notifications are sent on 2026-06-30.

Authors are invited to submit papers addressing any topic in statistical, structural or syntactic pattern recognition and their applications. Possible topics of interest include, but are not limited to: SPR Topics Classification; Prediction; Gaussian Processes Randomized Algorithms; Multiple Classifiers Ensemble Methods; Model Selection; Feature Selection Dimensionality Reduction; Dissimilarity Representations Metric Learning; Representation Learning Multiple Instance Learning; Clustering Semi Supervised learning; Weakly Supervised Learning Active Learning; Novelty Detection; Deep Learning Generative Models; Adversarial Learning Reinforcement Learning; Transfer Learning; Domain Adaptation; Data Complexity; Data Modeling SSPR Topics Structural Matching; Structural Complexity Syntactic Pattern Recognition Graph-theoretic Methods; Graph Neural Networks Graphical Models; Structural Kernels Spectral Methods Spatio-Temporal Pattern Recognition Structured Text Analysis Intelligent Sensing Systems Multimedia Analysis; Multimedia Retrieval Image Document Analysis; Image Understanding Shape Analysis
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