IEEE Transactions on Pattern Analysis - Impact Factor

IEEE Transactions on Pattern Analysis and Machine Intelligence | 2024 Impact Factor:18.6 | Cite Score:35.0 | Q1

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Impact Factor and Journal Rank of IEEE Transactions on Pattern Analysis and Machine Intelligence

About:IEEE Transactions on Pattern Analysis and Machine Intelligence(TPAMI) is a leading journal published by the IEEE Computer Society, dedicated to the fields of computer vision, machine learning, and pattern recognition. TPAMI is highly esteemed for its role in disseminating innovative research and developments that advance the understanding and application of pattern analysis and intelligent systems.
Objective: The primary aim of TPAMI is to publish high-quality, peer-reviewed research that contributes to the theoretical foundations, methodologies, and applications of pattern analysis and machine intelligence. The journal seeks to foster advancements in algorithms, models, and systems that enable computers to understand and interpret complex data.
Content: TPAMI features a wide range of scholarly content, including original research articles, survey papers, and critical reviews.
Interdisciplinary Focus: The journal embraces an interdisciplinary approach, integrating insights from computer science, engineering, mathematics, statistics, and cognitive sciences. This broad perspective enables TPAMI to address complex problems that require a multidisciplinary solution.
Global Reach and Impact: As part of the IEEE Computer Society, TPAMI attracts contributions from top researchers and institutions worldwide. This international dimension ensures a diverse range of perspectives and innovative solutions, enhancing the journals relevance and impact on a global scale.
High Standards and Rigorous Review: TPAMI maintains rigorous peer-review standards to ensure the publication of high-quality, impactful research. This commitment to excellence has established the journal as a trusted and influential resource in the fields of pattern analysis and machine intelligence.

Journal Home: Journal Homepage

Editor-in-Chief: Kyoung Mu Lee

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) is a prestigious journal within the field of computer vision, image processing, and pattern recognition. Its scope covers a wide range of topics related to the analysis, interpretation, and understanding of visual data.
Some key areas of interest include:
Computer Vision: This involves the extraction of meaningful information from images or videos, including topics such as object recognition, image segmentation, scene understanding, and visual tracking.
Image Processing: Techniques for manipulating and enhancing digital images, including methods for noise reduction, image restoration, image compression, and feature extraction.
Pattern Recognition: The study of algorithms and systems for recognizing patterns and making predictions based on observed data, encompassing areas such as machine learning, deep learning, statistical pattern recognition, and pattern classification.
Machine Learning for Vision: Development and application of machine learning algorithms for solving computer vision tasks, including supervised, unsupervised, and reinforcement learning approaches.
Biomedical Imaging: Applications of image analysis and machine learning techniques to medical imaging data, with a focus on tasks such as medical image segmentation, disease diagnosis, and image-guided therapy.
Document Analysis and Recognition: Techniques for automatically analyzing and recognizing text, handwriting, and other structured information in documents, including optical character recognition (OCR) and document layout analysis.