Conference Information

IPDL 2027: International Conference on Image Processing and Deep Learning

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Submission Date:
2027-01-09 Due in 95 days
Notification Date:
2027-03-09
Conference Date:
2027-04-23
Location:
Xi an, China
Years:
Viewed: 6809   Tracked: 0   Attend: 0
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IPDL
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Conference Partner Index (CP-I)

44.4 / 100
Ranked #3,086 of 5,693 conferences · Top 55%

#160 of 246 in Computer Vision & Pattern Recognition #355 of 742 in Artificial Intelligence & Machine Learning

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%)
37
Community attention (10%)
12
Public record completeness (15%)
55

Inputs used: Editions on record: 3 · Researchers who opened this page in the past 24 months: 4

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 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 2026-10-06

Call For Papers

IPDL 2027 (International Conference on Image Processing and Deep Learning) is an academic conference held in Xi an, China on 2027-04-23. The paper submission deadline is 2027-01-09. Acceptance notifications are sent on 2027-03-09.

The topics of interest for submission include, but are not limited to: 📚︎Image Processing · Image Enhancement and Denoising · Image Segmentation and Target Detection · Medical Image Processing · Remote Sensing Image Analysis · Image Compression and Coding · Image Restoration and Reconstruction · Image Style Migration · Video Analysis and Processing · Multimodal Image Processing · Image Quality Assessment · Face Recognition and Expression Analysis 📚︎Deep Learning · Deep Learning Basic Algorithms · Deep Learning in Computer Vision · Natural Language Processing combined with Vision · Migration Learning · Domain Adaptation · Augmented Learning · Federated Learning and Privacy Preservation · Self-supervised vs. unsupervised learning · Deep Learning Model Interpretability · Edge Computing;
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CSignal Processing: Image Communication2.7Elsevier0923-5965
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CKnowledge-Based Systems7.2Elsevier0950-7051
BSoftware & Systems Modeling3.2Springer1619-1366
AIEEE Transactions on Computers3.8IEEE0018-9340
CFuture Generation Computer Systems5.9Elsevier0167-739X
CNeurocomputing6.5Elsevier0925-2312
CPattern Recognition Letters3.9Elsevier0167-8655
BPattern Recognition7.6Elsevier0031-3203
IEEE Access3.6IEEE2169-3536

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