International Journal on Document Analysis and Recognition
metrics 2024
Empowering Knowledge through Document Insights
Introduction
International Journal on Document Analysis and Recognition (IJDAR), published by Springer Heidelberg, stands at the forefront of research and advancements in the field of document analysis, computer vision, and pattern recognition. With its ISSN 1433-2833 and E-ISSN 1433-2825, the journal is an essential resource for researchers and practitioners focusing on innovations in automatic document processing, image analysis, and artificial intelligence applications in document retrieval and recognition. Recognized as a Q1 journal in multiple relevant categories, including Computer Science Applications, Computer Vision and Pattern Recognition, and Software, IJDAR boasts impressive Scopus rankings that position it among the top-tier publications in these domains. The journal’s converged publication years from 1998 to 2024 offer a rich repository of knowledge essential for both theoretical and practical advancements, ensuring that researchers, professionals, and students can keep pace with the latest findings and methodologies. Access options may vary, but the journal continuously strives to facilitate the dissemination of high-quality research that contributes significantly to the academic discourse in document analysis and recognition.
Metrics 2024
Metrics History
Rank 2024
Scopus
IF (Web Of Science)
JCI (Web Of Science)
Quartile History
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