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AMTrans:Auto-Correlation Multi-Head Attention Transformer for Infrared Spectral Deconvolution

清华大学学报自然科学版（英文版） 2025年第3期30卷 1329-1341页

作者： Lei Gao Liyuan Cui Shuwen Chen Lizhen Deng Xiaokang Wang Xiaohong Yan Hu Zhu College of Electronic and Optical Engineering & College of Flexible Electronics(Future Technology) Nanjing University of Posts and TelecommunicationsNanjing 210003China Jiangsu Province Key Lab on Image Processing and Image Communication Nanjing University of Posts and TelecommunicationsNanjing 210003China National Engineering Research Center of Communication and Network Technology Nanjing University of Posts and TelecommunicationsNanjing 210003China School of Computer Science and Technology Hainan UniversityHaikou 570228China

Infrared spectroscopy analysis has found widespread applications in various fields due to advancements in technology and industry *** improve the quality and reliability of infrared spectroscopy signals,deconvolution is a crucial preprocessing *** by the transformer model,we propose an Auto-correlation Multi-head attention Transformer(AMTrans)for infrared spectrum sequence *** auto-correlation attention model improves the scaled dot-product attention in the *** utilizes attention mechanism for feature extraction and implements attention computation using the auto-correlation *** auto-correlation attention model is used to exploit the inherent sequence nature of spectral data and to effectively recovery spectra by capturing auto-correlation patterns in the *** proposed model is trained using supervised learning and demonstrates promising results in infrared spectroscopic *** comparing the experiments with other deconvolution techniques,the experimental results show that the method has excellent deconvolution performance and can effectively recover the texture details of the infrared spectrum.

关键词： spectroscopy spectral deconvolution transformer auto-correlation mechanism

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The NeRF Signature: Codebook-Aided Watermarking for Neural Radiance Fields

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IEEE Transactions on Pattern Analysis and Machine Intelligence 2025年第6期47卷 4652-4667页

作者： Ziyuan Luo Anderson Rocha Boxin Shi Qing Guo Haoliang Li Renjie Wan Department of Computer Science Hong Kong Baptist University Hong Kong SAR China Artificial Intelligence Lab. Recod.ai Institute of Computing University of Campinas Campinas Brazil State Key Laboratory of Multimedia Information Processing and National Engineering Research Center of Visual Technology School of Computer Science Peking University Beijing China IHPC and CFAR Agency for Science Technology and Research (A*STAR) Singapore Department of Electrical Engineering City University of Hong Kong Kowloon Hong Kong

Neural Radiance Fields (NeRF) have been gaining attention as a significant form of 3D content representation. With the proliferation of NeRF-based creations, the need for copyright protection has emerged as a critical issue. Although some approaches have been proposed to embed digital watermarks into NeRF, they often neglect essential model-level considerations and incur substantial time overheads, resulting in reduced imperceptibility and robustness, along with user inconvenience. In this paper, we extend the previous criteria for image watermarking to the model level and propose NeRF Signature, a novel watermarking method for NeRF. We employ a Codebook-aided Signature Embedding (CSE) that does not alter the model structure, thereby maintaining imperceptibility and enhancing robustness at the model level. Furthermore, after optimization, any desired signatures can be embedded through the CSE, and no fine-tuning is required when NeRF owners want to use new binary signatures. Then, we introduce a joint pose-patch encryption watermarking strategy to hide signatures into patches rendered from a specific viewpoint for higher robustness. In addition, we explore a Complexity-Aware key Selection (CAKS) scheme to embed signatures in high visual complexity patches to enhance imperceptibility. The experimental results demonstrate that our method outperforms other baseline methods in terms of imperceptibility and robustness.

关键词： Neural radiance field Watermarking Three-dimensional displays Training Robustness Pipelines Computational modeling Visualization Solid modeling Rendering (computer graphics)

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The scientific literature corpus for Chinese negation and uncertainty identification

The scientific literature corpus for Chinese negation and un...

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14th Workshop on Chinese Lexical Semantics, CLSW 2013

作者： Chen, Zhancheng Zou, Bowei Zhu, Qiaoming Li, Peifeng School of Computer Science and Technology Soochow University Jiangsu 215006 China Key Lab. of Computer Information Processing Technology of Jiangsu Province Suzhou Jiangsu 215006 China

ISBN: (纸本)9783642451843

Negative and uncertain expressions widely exist in natural language. Negation and uncertainty identification has become an important task in computational linguistics community. Lacking of corpus hinders the development of Chinese negation and uncertainty identification. This paper reports on a corpus annotation project for Chinese negation and uncertainty identification on scientific literature. We introduce several important aspects during our annotation, such as selection of raw text, framework of annotation, guidelines, data consistency and statistic data summarized from corpus. In this corpus, we annotate negation and uncertainty cues and their corresponding scopes. Statistic for corpus shows that there are a certain proportion of negative and uncertain expressions in Chinese scientific literature. Accordingly, this corpus is able to support the research of Chinese negation and uncertainty identification in the future. © 2013 Springer-Verlag.

关键词： Computational linguistics

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Chinese zero anaphor detection: Rule-based approach

Chinese zero anaphor detection: Rule-based approach

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作者： Qin, Kaiwei Kong, Fang Li, Peifeng Zhu, Qiaoming School of Computer Science and Technology Soochow University Jiangsu 215006 China Key Lab. of Computer Information Processing Technology of Jiangsu Province Suzhou Jiangsu 215006 China

ISBN: (纸本)9783642256608

A rule-based approach for Chinese zero anaphor detection is proposed. Given a parse tree, the smallest IP sub-tree covering the current predicate is captured. Based on this IP sub-tree, some rules are proposed for detecting whether a Chinese zero anaphor exists. This paper also systematically evaluates the rule-based method on OntoNotes corpus. Using golden parse tree, our method achieves 82.45 in F-measure. And the F-measure is 63.84 using automatic parser. The experiment results show that our method is very effective on Chinese zero anaphor detection. © 2011 Springer-Verlag Berlin Heidelberg.

关键词： Forestry

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A parallel ant colonies approach to de novo prediction of protein backbone in CASP8/9

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Science China(information Sciences) 2013年第10期56卷 226-238页

作者： LV Qiang WU HongJie WU JinZhen HUANG Xu LUO XiaoHu QIAN PeiDe School of Computer Science and Technology Soochow University Jiangsu Provincial Key Lab for Information Processing Technologies School of Electronic and Information Engineering Suzhou University of Science and Technology

Predicting the three-dimensional structure of proteins from amino acid sequences with only a few remote homologs,or de novo prediction,remains a major challenge in computational *** modeling of the protein backbone represents the initial phase of a protein structure prediction *** a parallel ant colony optimization based on sharing one pheromone matrix,this report proposes a parallel approach to predict the structure of a protein *** parallel approach combines various sources of energy functions and generates protein backbones with the lowest energies jointly determined by the various energy *** free modeling targets in CASP8/9 are used to evaluate the performance of the *** 13 targets in CASP8,two out of the predicted model1s selected by our approach are the best of the published CASP8 results,and seven out of the model1s are ranked in the top *** 29 targets in CASP9,20 out of the best models from our predictions are ranked in the top 10,and 11 out of the model1s are ranked in the top 10.

关键词： protein backbone prediction parallel ant colony optimization

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Improve tree kernel-based event pronoun resolution with competitive information

Improve tree kernel-based event pronoun resolution with comp...

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22nd International Joint Conference on Artificial Intelligence, IJCAI 2011

作者： Kong, Fang Zhou, Guodong JiangSu Provincial Key Lab. for Computer Information Processing Technology School of Computer Science and Technology Soochow University China

ISBN: (纸本)9781577355120

Event anaphora resolution plays a critical role in discourse analysis. This paper proposes a tree kernel- based framework for event pronoun resolution. In particular, a new tree expansion scheme is introduced to automatically determine a proper parse tree structure for event pronoun resolution by considering various kinds of competitive information related with the anaphor and the antecedent candidate. Evaluation on the OntoNotes English corpus shows the appropriateness of the tree kernel-based framework and the effectiveness of competitive information for event pronoun resolution.

关键词： Trees (mathematics)

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A tree kernel-based unified framework for Chinese zero anaphora resolution

A tree kernel-based unified framework for Chinese zero anaph...

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Conference on Empirical Methods in Natural Language processing, EMNLP 2010

作者： Kong, Fang Zhou, Guodong JiangSu Provincial Key Lab. for Computer Information Processing Technology School of Computer Science and Technology Soochow University China

ISBN: (纸本)1932432868

This paper proposes a unified framework for zero anaphora resolution, which can be divided into three sub-tasks: zero anaphor detection, anaphoricity determination and antecedent identification. In particular, all the three sub-tasks are addressed using tree kernel-based methods with appropriate syntactic parse tree structures. Experimental results on a Chinese zero anaphora corpus show that the proposed tree kernel-based methods significantly outperform the feature-based ones. This indicates the critical role of the structural information in zero anaphora resolution and the necessity of tree kernel-based methods in modeling such structural information. To our best knowledge, this is the first systematic work dealing with all the three sub-tasks in Chinese zero anaphora resolution via a unified framework. Moreover, we release a Chinese zero anaphora corpus of 100 documents, which adds a layer of annotation to the manually-parsed sentences in the Chinese Treebank (CTB) 6.0. © 2010 Association for Computational Linguistics.

关键词： Trees (mathematics)

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Content-based image retrieval using fuzzy hamming distance

Content-based image retrieval using fuzzy hamming distance

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2007 8th International Conference on Electronic Measurement and Instruments, ICEMI

作者： Hu, Xuelong Yang, Li Zhang, Gensheng School of Information Engineering Yangzhou University Yangzhou 225009 China Jiangsu Province Key Lab. for Image Processing and Communication Nanjing University of Post and Telecommunications Nanjing 215006 China Jiangsu Province Key Lab. for Computer Information Processing Technology Suzhou University Suzhou 215006 China

ISBN: (纸本)1424411351

This paper addresses an effective issue of content-based image retrieval (CBIR) by presenting Fuzzy Hamming Distance (FHD). Firstly, the theory of FHD is introduced, which includes degree of difference and cardinality of the fuzzy set, and then follows defuzzification of FHD which is used as a fuzzy similarity measure. In the experiment, the image retrieval results show this method can be employed to capture implicitly some semantic contents of the image in addition to other features such as color, texture and shape. Finally, an implemented prototype system demonstrates a promising retrieval performance for a test database, as compared with FUZZYCLUB system. © 2007 IEEE.

关键词： Hamming distance

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A new method for semi-automatic image annotation

A new method for semi-automatic image annotation

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2007 8th International Conference on Electronic Measurement and Instruments, ICEMI

作者： Xuelong, Hu Yuhui, Zhang Li, Yang School of Information Engineering Yangzhou University Yangzhou 225009 China Jiangsu Province Key Lab. of Image Processing and Communication Nanjing University of Post and Telecommunications Nanjing 215006 China Jiangsu Province Key Lab. of Computer Information Processing Technology Suzhou University Suzhou 215006 China

ISBN: (纸本)1424411351

Semantic-based image retrieval bridges the gap between visual features and human understanding of image in the field of image retrieval. Image annotation is one important technology of image retrieval based on the semantic. This paper proposed one method to realize semi-automatic image annotation with the tool Support Vector Machine (SVM). The image collection was divided into two parts, one for manual annotation and the other for testing. After being classified by SVM, the output was changed into a probability, and K-NN algorithm was applied to get the keywords for unlab.led images. The experiments show that the approach is feasible. © 2007 IEEE.

关键词： Support vector machines

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A Fast Calculation of Metric Scores for Learning Bayesian Network

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International Journal of Automation and computing 2012年第1期9卷 37-44页

作者： Qiang Lv Xiao-Yan Xia Pei-De Qian School of Computer Science and Technology Soochow University Suzhou 215006 PRC Jiangsu Provincial Key Lab for Computer Information Processing Technology Suzhou 215006 PRC

Frequent counting is a very so often required operation in machine learning algorithms. A typical machine learning task, learning the structure of Bayesian network （BN） based on metric scoring, is introduced as an example that heavily relies on frequent counting. A fast calculation method for frequent counting enhanced with two cache layers is then presented for learning BN. The main contribution of our approach is to eliminate comparison operations for frequent counting by introducing a multi-radix number system calculation. Both mathematical analysis and empirical comparison between our method and state-of-the-art solution are conducted. The results show that our method is dominantly superior to state-of-the-art solution in solving the problem of learning BN.

关键词： Frequent counting radix-based calculation ADtree learning Bayesian network metric score

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