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This three-volume set LNCS 14406-14408 constitutes the refereed proceedings of the 7th Asian Conference on Pattern Recognition, ACPR 2023, held in Kitakyushu, Japan, in November 2023. The 93 full papers presented were carefully reviewed and selected from 164 submissions. The conference focuses on four important areas of pattern recognition: pattern recognition and machine learning, computer vision and robot vision, signal processing, and media processing and interaction, covering various technical aspects.

Artificial intelligence. --- Application software. --- Pattern recognition systems. --- Artificial Intelligence. --- Computer and Information Systems Applications. --- Automated Pattern Recognition. --- Computer vision --- Pattern recognition systems --- Signal processing

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This three-volume set LNCS 14406-14408 constitutes the refereed proceedings of the 7th Asian Conference on Pattern Recognition, ACPR 2023, held in Kitakyushu, Japan, in November 2023. The 93 full papers presented were carefully reviewed and selected from 164 submissions. The conference focuses on four important areas of pattern recognition: pattern recognition and machine learning, computer vision and robot vision, signal processing, and media processing and interaction, covering various technical aspects.

Artificial intelligence. --- Application software. --- Pattern recognition systems. --- Artificial Intelligence. --- Computer and Information Systems Applications. --- Automated Pattern Recognition. --- Computer vision --- Pattern recognition systems --- Signal processing

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Identifying plagiarism is a pressing problem for research institutions, publishers, and funding bodies. Current detection methods focus on textual analysis and find copied, moderately reworded, or translated content. However, detecting more subtle forms of plagiarism, including strong paraphrasing, sense-for-sense translations, or the reuse of non-textual content and ideas, remains a challenge. This book presents a novel approach to address this problem—analyzing non-textual elements in academic documents, such as citations, images, and mathematical content. The proposed detection techniques are validated in five evaluations using confirmed plagiarism cases and exploratory searches for new instances. The results show that non-textual elements contain much semantic information, are language-independent, and resilient to typical tactics for concealing plagiarism. Incorporating non-textual content analysis complements text-based detection approaches and increases the detection effectiveness, particularly for disguised forms of plagiarism. The book introduces the first integrated plagiarism detection system that combines citation, image, math, and text similarity analysis. Its user interface features visual aids that significantly reduce the time and effort users must invest in examining content similarity. About the author Norman Meuschke is a Senior Researcher for Information Retrieval and Natural Language Processing at the University of Göttingen, Germany.

Natural language processing (Computer science). --- Image processing—Digital techniques. --- Computer vision. --- Pattern recognition systems. --- Natural Language Processing (NLP). --- Computer Imaging, Vision, Pattern Recognition and Graphics. --- Automated Pattern Recognition. --- NLP (Computer science) --- Artificial intelligence --- Electronic data processing --- Human-computer interaction --- Semantic computing --- Pattern classification systems --- Pattern recognition computers --- Pattern perception --- Computer vision --- Machine vision --- Vision, Computer --- Image processing --- Pattern recognition systems

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This two volume set (CCIS 1776-1777) constitutes the refereed proceedings of the 7th International Conference on Computer Vision and Image Processing, CVIP 2022, held in Nagpur, India, November 4–6, 2022. The 110 full papers and 11 short papers were carefully reviewed and selected from 307 submissions. Out of 121 papers, 109 papers are included in this book. The topical scope of the two-volume set focuses on Medical Image Analysis, Image/ Video Processing for Autonomous Vehicles, Activity Detection/ Recognition, Human Computer Interaction, Segmentation and Shape Representation, Motion and Tracking, Image/ Video Scene Understanding, Image/Video Retrieval, Remote Sensing, Hyperspectral Image Processing, Face, Iris, Emotion, Sign Language and Gesture Recognition, etc.

Image processing—Digital techniques. --- Computer vision. --- Computer Imaging, Vision, Pattern Recognition and Graphics. --- Machine vision --- Vision, Computer --- Artificial intelligence --- Image processing --- Pattern recognition systems

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This book constitutes the First Left Atrial and Scar Quantification and Segmentation Challenge, LAScarQS 2022, which was held in conjunction with the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, in Singapore, in September 2022. The 15 papers presented in this volume were carefully reviewed and selected form numerous submissions. The aim of the challenge is not only benchmarking various LA scar segmentation algorithms, but also covering the topic of general cardiac image segmentation, quantification, joint optimization, and model generalization, and raising discussions for further technical development and clinical deployment.

Image processing—Digital techniques. --- Computer vision. --- Computer Imaging, Vision, Pattern Recognition and Graphics. --- Machine vision --- Vision, Computer --- Artificial intelligence --- Image processing --- Pattern recognition systems