Imaging Science Journal, published by Taylor & Francis Ltd, serves as a vital resource for researchers and professionals in the fields of computer vision, pattern recognition, and media technology. With an ISSN of 1368-2199 and an E-ISSN of 1743-131X, this journal has been fostering scholarly dialogue since its inception in 1997, with a converged content offering extending through 2024. Its categorization in Quartile 4 in Computer Vision and Pattern Recognition and Quartile 3 in Media Technology highlights its relevance and contributions to emerging trends in these domains. Although it ranks 36th in the Engineering - Media Technology category and 96th in Computer Science - Computer Vision and Pattern Recognition, its innovative research and insights continue to attract the attention of scholars dedicated to advancing knowledge at the intersection of imaging technologies. Offering versatile access options, this journal is essential for students, researchers, and professionals aiming to stay informed and engaged in the rapidly evolving landscape of imaging science.

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.

The International Journal of Neural Systems, published by World Scientific Publishing Co Pte Ltd, is a prestigious peer-reviewed journal dedicated to the dynamic field of neural systems research. With an ISSN of 0129-0657 and an E-ISSN of 1793-6462, this journal serves as a vital resource for researchers, professionals, and students interested in the intersections of computer science, neural networks, and communications. Noteworthy for its impact, the journal has achieved impressive rankings in 2023, positioned in the Q1 quartile for both Computer Networks and Communications as well as in the miscellaneous category of Medicine, highlighting its interdisciplinary significance and broad relevance. The journal's Scopus rank places it at #33 out of 395 in its category, reflecting its influence and reach within the academic community. While the journal is not open access, its contributions to advancing the understanding of neural systems are invaluable, offering a platform for disseminating cutting-edge research and fostering collaboration among scholars. Since its inception, the International Journal of Neural Systems remains committed to excellence and innovation in its published content, making it an essential subscription for everyone involved in this exciting and rapidly evolving field.

Machine Intelligence Research is a premier academic journal published by SPRINGERNATURE, dedicated to advancing knowledge in the rapidly evolving fields of Artificial Intelligence, Applied Mathematics, and more. With its ISSN 2731-538X and E-ISSN 2731-5398, the journal is recognized for its impact, holding a distinguished position in various Q1 categories for 2023, including Computer Vision and Pattern Recognition and Control and Systems Engineering. Operating under an Open Access model, it ensures that groundbreaking research from China and around the world remains accessible to a global audience, promoting collaboration and innovation. As a beacon for researchers, professionals, and students, Machine Intelligence Research aims to disseminate high-quality research findings, innovative methodologies, and influential theories, thereby shaping the future landscapes of science and technology.

INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, published by WORLD SCIENTIFIC PUBL CO PTE LTD, is a prestigious academic journal established in 1995 that serves as a critical platform for disseminating innovative research in the rapidly evolving fields of artificial intelligence, pattern recognition, and computer vision. With a focus on advancing theoretical and applied methodologies, the journal aims to bridge the gap between research and practical applications, making it essential reading for researchers, professionals, and students alike. The journal holds strong rankings within its categories, placing it in the Q4 for Artificial Intelligence, Q3 for Computer Vision and Pattern Recognition, and Q3 for Software as of 2023. Despite its growing influence, it continues to provide a rich resource for studies at the intersection of machine learning and computer science. The INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE not only contributes to academic discourse but also acts as a catalyst for technological advancement, making a significant impact on the scientific community.

CAAI Transactions on Intelligence Technology is a premier peer-reviewed journal published by WILEY, dedicated to advancing the fields of Artificial Intelligence, Computer Networks and Communications, Computer Vision and Pattern Recognition, Human-Computer Interaction, and Information Systems. Since its inception in 2017, this Open Access journal has rapidly ascended the ranks, achieving Q1 quartile status across multiple categories as of 2023, and is recognized for its rigorous standards and innovative research dissemination, evidenced by impressive Scopus rankings, including Rank #12 in Computer Vision and Pattern Recognition. Through its commitment to providing a platform for high-quality research, the journal invites contributions from scholars globally, fostering a collaborative environment that stimulates intellectual exchange and encourages advancements in intelligent technology. Addressed to researchers, professionals, and students alike, CAAI Transactions on Intelligence Technology serves as a vital resource for those aiming to stay at the forefront of technological innovation.

Image and Vision Computing, published by Elsevier, serves as a leading international journal focused on the dynamic fields of computer vision, pattern recognition, and signal processing. With its esteemed Q1 category rankings in these areas and an impressive standing in Scopus metrics, where it ranks 19th in Computer Vision and 23rd in Signal Processing, this journal has firmly positioned itself at the forefront of academic research and innovation. Established in 1983, it continues to publish cutting-edge research that drives advancements in technology and applications across various domains. The journal is committed to disseminating high-quality, peer-reviewed articles that address significant challenges and propose novel solutions, making it an essential resource for researchers, practitioners, and students alike. While not an open access journal, Image and Vision Computing offers a wealth of valuable insights into the ever-evolving landscape of visual computing technologies.

VISUAL COMPUTER is a prestigious journal published by Springer, focusing on the dynamic fields of computer graphics, computer-aided design, computer vision, and software. Established in 1985, this interdisciplinary journal serves as a vital platform for sharing innovative research, applications, and developments crucial to the advancement of visual computing technologies. With a notable Q2 ranking in various categories, including Computer Graphics and Computer-Aided Design, and Computer Vision and Pattern Recognition, VISUAL COMPUTER demonstrates a solid impact within the academic community, marked by its Scopus rankings that reflect its significant contributions to the field. While the journal does not offer open access, it remains a reliable source of high-quality content for researchers, professionals, and students eager to stay abreast of emerging trends and techniques, ultimately fostering collaboration and knowledge exchange within the rapidly evolving landscape of visual computing.

Acta Universitatis Sapientiae Informatica, published by SCIENDO, is an esteemed open-access journal in the field of computer science and informatics. Since its transition to open access in 2013, the journal has fostered an inclusive academic environment that allows researchers, professionals, and students to freely access cutting-edge research and innovations. With its ISSN 1844-6086 and E-ISSN 2066-7760, Acta Universitatis Sapientiae Informatica aims to disseminate high-quality scholarly articles that cover a broad scope of topics ranging from theoretical foundations to practical applications in informatics. Located in Warsaw, Poland, the journal serves as an essential platform for advancing the discourse in computer science, thus playing a critical role in both regional and international research communities.

MACHINE VISION AND APPLICATIONS is a distinguished peer-reviewed journal published by SPRINGER, serving as a vital platform for innovative research in the fields of computer vision, pattern recognition, and their applications within hardware and software systems. Since its inception in 1988, the journal has been at the forefront of disseminating cutting-edge findings and advances in machine vision technologies, significantly contributing to the global academic discourse. With an impressive track record, the journal ranks in the Q2 category across various domains in the 2023 Scopus rankings, reflecting its esteemed position in Computer Science Applications, Computer Vision and Pattern Recognition, Hardware and Architecture, and Software. Although it does not currently offer open access options, MACHINE VISION AND APPLICATIONS remains a critical resource for researchers, professionals, and students eager to explore emerging trends and methodologies in the rapidly evolving landscape of machine vision.