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Enhanced oracle bone corrosion detection using attention-guided YOLO with ghost convolution

Discover Artificial Intelligence 2024年第1期4卷 1-13页

作者： Gao, Feng Yang, Ziheng Liu, Qiyu Zhang, Zhan Li, Bang Zhang, Han Key Laboratory of Oracle Bone Inscriptions Information Processing Ministry of Education Anyang455000 China School of Computer & Information Engineering Anyang Normal University Henan Anyang455000 China

oracle bone inscriptions (OBIs), as the important records of early Chinese characters, possess profound cultural and historical significance. However, These fragments are susceptible to further damage due to corrosion. Consequently, the identification and localization of corroded regions on these fragments to prevent further deterioration has emerged as a critical task. Current object detection algorithms exhibit limitations in identifying corroded regions on oracle bone fragments, which is manifested by suboptimal detection accuracy, F1 scores, and average precision (AP) values. This deficiency hinders their capability to effectively manage the complexity and diversity of corrosion patterns present on oracle bone fragments. To tackle this challenge, this study incorporates advanced attention mechanisms, including Squeeze-and-Excitation Networks (SE), Coordinate attention, and Convolutional Block Attention Module (CBAM), into the YOLOv5 detection architecture. Additionally, we introduce Ghost convolution into the backbone network to effectively retain critical feature map information while optimizing computational efficiency. Our experimental results indicate that the integration of CBAM attention and Ghost convolution within the YOLOv5 backbone markedly improves the detection accuracy of corroded regions on oracle bone fragments. Specifically, compared to the baseline YOLOv5 model, the proposed models incorporating SE, CBAM, and Ghost convolution obtain the improvements of 2.2%, 6.3%, and 8.5% in AP, respectively. This improvement in detection performance not only facilitates the identification of corroded areas but also contributes to the preservation of oracle bone heritage and the continuity of cultural knowledge. © The Author(s) 2024.

关键词： Object detection

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oraclePoints: A Hybrid Neural Representation for oracle Character 23

OraclePoints: A Hybrid Neural Representation for Oracle Char...

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31st ACM International Conference on Multimedia, MM 2023

作者： Jiang, Runhua Liu, Yongge Zhang, Boyuan Chen, Xu Li, Deng Han, Yahong College of Intelligence and Computing Tianjin University Tianjin China School of Computer and Information Engineering Anyang Normal University Anyang China Key Laboratory of Oracle Bone Inscriptions Information Processing Ministry of Education Anyang China

ISBN: (纸本)9798400701085

oracle bone inscriptions (OBI) are ancient hieroglyphs originated in China and are considered one of the most famous writing systems in the world. Up to now, thousands of OBIs have been discovered, which require deciphering by experts to understand their contents. Experts typically need to restore, classify, and compare each character with previous inscriptions. Although existing research can assist with one of these operations, their performance falls short of practical requirements. In this work, we propose the oraclePoints framework, which represents OBI images as hybrid neural representations comprising features of images and point sets. The image representation provides inscription appearance and character structure, while the point representation makes it easy and effective to distinguish characters and noises. In addition, we demonstrate that oraclePoints can be easily integrated with existing models in a plug-and-play manner. Comprehensive experiments demonstrate that the proposed hybrid neural representation framework supports a range of OBI tasks, including character image retrieval, recognition, and denoising. It is also demonstrated that oraclePoints is helpful for deciphering OBIs by linking ancient characters to modern Chinese characters. Our codes are available at https://***/. © 2023 ACM.

关键词： Geometry

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Research on oracle bone inscriptions Recognition From Multi-Source Data Based on Deep Learning 7

Research on Oracle Bone Inscriptions Recognition From Multi-...

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7th IEEE Advanced information Technology, Electronic and Automation Control Conference, IAEAC 2024

作者： Wang, Nan Qi, Zhenyang Du, Fengxia Anyang Normal University School of Computer & Information Engineering Henan Anyang455000 China Ministry of Education of China Key Laboratory of Oracle Bone Inscriptions Information Processing Henan Anyang455000 China Anyang Normal University School of Fine Art Henan Province Anyang455000 China

ISBN: (纸本)9798350339161

How to carry out recognition process in a quick and effective way is important to the oracle bone inscriptions research area. In this paper, we proposed a recognition method which adopt a skeletonization process to normalize handwriting and rubbing forms of oracle bone inscriptions into the same expression. Then by using models based on CNN such as VGG19, AlexNet and ResNet34, the proposed method can simultaneously handle recognition work with mixed input. The experiment results showed that our method achieve a good performance applied in the real oracle bone inscriptions data set. © 2024 IEEE.

关键词： Deep learning

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ViT-based Classification of oracle bones for Periodization of the Shang Dynasty

ViT-based Classification of Oracle Bones for Periodization o...

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2023 International Conference on Algorithms, High Performance Computing, and Artificial Intelligence, AHPCAI 2023

作者： Li, Bang Ding, Zengmao Zheng, Rongxin Han, Shengwei Zhang, Han Zhang, Zhan Guo, An Wang, Nan Gao, Feng Liu, Yongge School of Computer & Information Engineering Anyang Normal University Henan Anyang455000 China Key Laboratory of Oracle Bone Inscriptions Information Processing Ministry of Education of China Henan Anyang455000 China International Joint Research Laboratory for Perception Data Intelligent Processing of Henan Anyang Normal University Henan Anyang455000 China

ISBN: (纸本)9781510671881

oracle bone inscriptions are the oldest systematically written characters in China, and their periodization and chronology are essential tasks in historical research. However, current deep-learning models face significant challenges when they are used to recognize oracle bone images directly. These models can only achieve an accuracy of no more than 45%. As the research on the periodization of oracle bones mainly relies on the characters inscribed on the bones, a domain knowledge-based oracle bone classification model is proposed that improves the recognition accuracy of Vision Transformer (ViT) by 5.28%. The proposed approach incorporates results obtained from oracle bone character detection to provide a more effective recognition object. Moreover, a novel model with a style network and category embedding is proposed in this paper that focuses on characters, resulting in a notable improvement in recognition accuracy of 16.01%. Our study reveals the importance of domain knowledge in the classification of historical documents, and it presents new insights into using artificial intelligence for assisting in historical document organization tasks. © 2023 SPIE. All rights reserved.

关键词： Domain Knowledge

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Plasmon-enhanced photoresponse of deep-subwavelength GaAs NW photodetector

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Optoelectronics Letters 2021年第7期17卷 385-389页

作者： LI Bang TANG Yanni YAN Xin ZHANG Xia LIU Yongg School of Computer&Information Engineering Anyang Normal UniversityAnyang 455000China Key Laboratory of Oracle Bone Inscriptions Information Processing Ministry of Education of ChinaAnyang 455000China Henan Key Laboratory of Oracle Bone Inscriptions Information Processing Anyang 455000China State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and TelecommunicationsBeijing 100876China

According to optical diffraction limit, the photoresponsity of nanowire(NW)-based photodetector exponentially decreases when its NW diameter reduces to the range of deep subwavelength. In this paper, we demonstrate a photoresponse-enhanced method of the deep-subwavelength Ga As NW photodetector by using a plasmon-driven dipole antenna. Considering that the enhancement is extremely influenced by the shape and size of antenna, the structure of antenna is optimized by finite difference time domain(FDTD) solutions. The optimal structure of antenna optimizes the responsivity-enhanced factors to 1123.3 and 224.7 in NW photodetectors with NW diameters of 20 nm and 60 nm, respectively. This photoresponse-enhanced method is promising for easy-integration high-performance nanoscale photodetectors.

关键词： antenna photoresponse photodetector

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Construction of Chinese Character Semantic Knowledge Graph for Overseas Chinese Learners

Construction of Chinese Character Semantic Knowledge Graph f...

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2022 International Conference on Computer Engineering and Artificial Intelligence, ICCEAI 2022

作者： Xiong, Jing Liu, Guoying Guo, Tao Chen, Yining Ministry of Education Engineering Research Center of Oracle Bone Culture Intelligent Industry Anyang Normal University Sch. of Comp. and Info. Eng. Key Laboratory of Oracle Bone Inscriptions Information Processing Anyang China

ISBN: (数字)9781665468039

ISBN: (纸本)9781665468039

Chinese characters have a long history and have been used until now. In recent years, they have attracted more and more foreigners to learn and use. However, traditional methods of Chinese character learning have a long cycle and are difficult. If we can understand the meaning of Chinese characters and form a knowledge group of them with relevant meanings, it can effectively improve learning efficiency. We achieve this goal by building a Chinese character semantic knowledge graph aims at organizing Chinese characters with semantic relevance together to facilitate the learners to understand. In the process of building the knowledge graph, the semantic computing capacity of HowNet was utilized, and 104187 associated edges were finally established for 6752 Chinese characters. Its scale meets the needs of overseas Chinese learners. © 2022 IEEE.

关键词： Knowledge graph

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oracle Character Prototype-Guided Cyclic Disentanglement for oracle bone inscriptions Detection 4th

Oracle Character Prototype-Guided Cyclic Disentanglement for...

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4th International Conference on Pattern Recognition and Artificial Intelligence, ICPRAI 2024

作者： Li, Bang Zhang, Jingping Yu, Nana Zhang, Zihao Liu, Yongge Han, Yahong School of Computer and Information Engineering Anyang Normal University Anyang455000 China Key Laboratory of Oracle Bone Inscriptions Information Processing Ministry of Education Anyang455000 China Digital Media Art Department Shanghai Theatre Academy Shanghai200040 China Key Laboratory of Integrated Innovation of Digital Performing Arts Ministry of Culture and Tourism Shanghai200040 China College of Intelligence and Computing Tianjin University Tianjin300072 China

ISBN: (纸本)9789819787043

oracle bone inscriptions (OBI), as the oldest form of Chinese writing, bears the precious heritage of ancient Chinese civilization. Deciphering OBI has been a monumental challenge in archaeology and philology. However, the preservation method of OBI through rubbings faces significant challenges due to severe noise interference, adversely affecting the accuracy of OBI detection. Additionally, existing traditional object detection algorithms inadequately consider the unique characteristics of OBI, making it difficult to effectively identify oracle characters on OBI rubbings. To address these challenges, this paper proposes a novel approach to OBI detection, oracle Character Prototype-guided cyclic disentanglement for OBI detection. These features are amalgamated into distinct character structure prototypes by capturing shared character structure features among different oracle characters. This approach highlights the distinctive forms of oracle characters, enhancing feature clarity and recognition. The oracle Character Prototypes enable the model to learn common features across different character forms, improving its adaptability to various oracle character structures and enhancing its capability to handle complexity. Moreover, to mitigate the impact of noise on detection, we introduce a cyclic disentanglement method for oracle bone inscriptions. This process, utilizing the oracle Character Prototypes and contrastive loss as supervisory signals, cyclically decouples oracle features, isolating information rich in character structure features. This effectively mitigates the influence of noise on OBI detection. Comprehensive evaluations were conducted, comparing our method with state-of-the-art object detection algorithms, validating its effectiveness both qualitatively and quantitatively. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Object detection

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oracle bone inscriptions Detection Based On Standard Evaluation Metric

Oracle Bone Inscriptions Detection Based On Standard Evaluat...

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Image processing, Computer Vision and Machine Learning (ICICML), International Conference on

作者： Peige Zhao Yongge Liu School of Computer and Artificial Intelligence Zhengzhou University Oracle Bone Inscriptions Information Processing Ministry of Education of China School of Computer and information Engineering Anyang Normal University Key Laboratory of Oracle Bone Inscriptions Information Processing Ministry of Education of China

ISBN: (纸本)9781665464697

Just like ImageNet in its time, MS COCO has become the standard for object detection today. Naturally, the evaluation metric of MS COCO also become the standard. However, the previous evaluation metrics for the detection of oracle bone inscriptions (OBIs) are the precision, recall and F-measure. So, they will fail to evaluate one detector comprehensively and fairly. This paper uses the standard evaluation metric of object detection in MS COCO to evaluate the performance of various models for detecting oracle bone inscriptions (OBIs).

关键词： Measurement Technological innovation Computer vision Image processing Computational modeling Detectors Object detection

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Research on inscription rubbings text detection based on deep learning 2021

Research on inscription rubbings text detection based on dee...

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4th International Conference on information Systems and Computer Aided Education, ICISCAE 2021

作者： Song, Xu Liu, Guoying Wang, Zhiyin School of Computer and Information Engineering Anyang Normal University Anyang China Key Laboratory of Oracle Bone Inscriptions Information Processing Ministry of Education Anyang China

ISBN: (纸本)9781450390255

It is of great practical significance to use advanced digital and intelligent technology to digitally apply and effectively protect China's ancient cultural heritage and resolve the problems that cannot be solved by manpower in a faster and more efficient way. Based on the YOLOv4 target detection algorithm, this paper effectively expands the collected data according to the data characteristics of inscription rubbings and text images, and carries out many training and verification tests. The accuracy of the detection model is 92.3%, so as to improve the speed and quality of rubbing arrangement of inscriptions. © 2021 ACM.

关键词： Deep learning

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Typos Correction in Overseas Chinese Learning Based on Chinese Character Semantic Knowledge Graph

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Journal of Data Analysis and information processing 2023年第2期11卷 200-216页

作者： Jing Xiong Xue Zhai Zhan Zhang Feng Gao School of Computer and Information Engineering Anyang Normal University Anyang China Key Laboratory of Oracle Bone Inscriptions Information Processing Ministry of Education Anyang China School of Civil Engineering and Architecture Anyang Normal University Anyang China

In recent years, more and more foreigners begin to learn Chinese characters, but they often make typos when using Chinese. The fundamental reason is that they mainly learn Chinese characters from the glyph and pronunciation, but do not master the semantics of Chinese characters. If they can understand the meaning of Chinese characters and form knowledge groups of the characters with relevant meanings, it can effectively improve learning efficiency. We achieve this goal by building a Chinese character semantic knowledge graph (CCSKG). In the process of building the knowledge graph, the semantic computing capacity of HowNet was utilized, and 104,187 associated edges were finally established for 6752 Chinese characters. Thanks to the development of deep learning, OpenHowNet releases the core data of HowNet and provides useful APIs for calculating the similarity between two words based on sememes. Therefore our method combines the advantages of data-driven and knowledge-driven. The proposed method treats Chinese sentences as subgraphs of the CCSKG and uses graph algorithms to correct Chinese typos and achieve good results. The experimental results show that compared with keras-bert and pycorrector + ernie, our method reduces the false acceptance rate by 38.28% and improves the recall rate by 40.91% in the field of learning Chinese as a foreign language. The CCSKG can help to promote Chinese overseas communication and international education.

关键词： Chinese Character Meaning Knowledge Graph Typos Correction OpenHowNet Semantic Relevancy

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