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arXiv 2024年

作者： Tu, Shuyuan Dai, Qi Zhang, Zihao Xie, Sicheng Cheng, Zhi-Qi Luo, Chong Han, Xintong Wu, Zuxuan Jiang, Yu-Gang Shanghai Key Lab of Intell. Info. Processing School of CS Fudan University China Shanghai Collaborative Innovation Center of Intelligent Visual Computing China Microsoft Research Asia China Carnegie Mellon University United States Huya Inc.

Despite impressive advancements in diffusion-based video editing models in altering video attributes, there has been limited exploration into modifying motion information while preserving the original protagonist's appearance and background. In this paper, we propose MotionFollower, a lightweight score-guided diffusion model for video motion editing. To introduce conditional controls to the denoising process, MotionFollower leverages two of our proposed lightweight signal controllers, one for poses and the other for appearances, both of which consist of convolution blocks without involving heavy attention calculations. Further, we design a score guidance principle based on a two-branch architecture, including the reconstruction and editing branches, which significantly enhance the modeling capability of texture details and complicated backgrounds. Concretely, we enforce several consistency regularizers and losses during the score estimation. The resulting gradients thus inject appropriate guidance to the intermediate latents, forcing the model to preserve the original background details and protagonists' appearances without interfering with the motion modification. Experiments demonstrate the competitive motion editing ability of MotionFollower qualitatively and quantitatively. Compared with MotionEditor, the most advanced motion editing model, MotionFollower achieves an approximately 80% reduction in GPU memory while delivering superior motion editing performance and exclusively supporting large camera movements and *** Codes 68T45, 68T10 Copyright © 2024, The Authors. All rights reserved.

关键词： Diffusion

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A database encryption scheme based on the generalized aryabhata remainder theorem

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Journal of Information Hiding and Multimedia signal processing 2014年第4期5卷 603-613页

作者： Liu, Yanjun Liu, Yanjun Chang, Chin-Chen Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei230039 China Department of Computer Science and Information Engineering Asia University Taichung413 Taiwan No.26 Hexing Road Xiangfang District Harbin China Department of Information Engineering and Computer Science Feng Chia University Taichung407 Taiwan

Database security prevents the disclosure of confidential data within a database to unauthorized users, and has become an urgent challenge for a tremendous number of database applications. Data encryption is a widely-used cryptographic technique for realizing database security in which the data kept in the database are encrypted into ciphertext. Inspired by Lin et al.’s database encryption system, we propose a record-oriented database encryption scheme based on the Generalized Aryabhata Remainder Theorem (GART). Analysis showed that our proposed scheme is more efficient than Lin et al.’s scheme, while retaining the same security. ©2014.

关键词： Database systems

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Application of community detection algorithm with link clustering in inhibition of social network worms

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International Journal of Network Security 2017年第3期19卷 458-468页

作者： Wang, Yibing Fang, Jie Wu, Fuhu Center of Computer Teaching Anhui University No.111 Jiulong Road Hefei Anhui236061 China School of Electronics and Information Engineering Chinese Academy of Sciences No.350 Shushanhu Road Hefei Anhui230031 China Key Laboratory of Intelligent Computing Signal Processing of Ministry of Education Anhui University No.3 Feixi Road Hefei Anhui230039 China

The community detection was performed from the perspective of links, and we proposed an inhibition method against social network worms. Firstly, a community detection algorithm was proposed, which based on link clustering, and we got related link incremental information through the network structure information at various time points. In order to obtain the link communities, we adopted an improved link partition density function to dispose the link incremental information. Next, we gave three selection strategies of key nodes in community and proposed corresponding worm inhibition method. Finally, on the basis of real web data sets, we applied community detection and worm inhibition experiments to prove validity of algorithm in this paper.

关键词： signal detection

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On self-dual four circulant codes

arXiv

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arXiv 2017年

作者： Shi, Minjia Zhu, Hongwei Solé, Patrick Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University No. 3 Feixi Road Hefei230039 China School of Mathematical Sciences of Anhui University Hefei230601 China CNRS/LAGA University of Paris 8 2 rue de la liberté Saint-Denis93 526 France

Four circulant codes form a special class of 2-generator, index 4, quasi-cyclic codes. Under some conditions on their generator matrices they can be shown to be self-dual. Artin primitive root conjecture shows the existence of an infinite subclass of these codes satisfying a modified Gilbert-Varshamov bound. Copyright © 2017, The Authors. All rights reserved.

关键词： Block codes

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A new approach to the Kasami codes of type 2

arXiv

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arXiv 2018年

作者： Shi, Minjia Krotov, Denis S. Solé, Patrick The Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education School of Mathematics Anhui University Anhui230601 China The Sobolev Institute of Mathematics pr. Akademika Koptyuga 4 Novosibirsk630090 Russia The CNRS LAGA University of Paris 8 2 rue de la Liberté Saint-Denis93 526 France

The dual of the Kasami code of length q2 − 1, with q a power of 2, is constructed by concatenating a cyclic MDS code of length q + 1 over Fq with a Simplex code of length q − 1. This yields a new derivation of the weight distribution of the Kasami code, a new description of its coset graph, and a new proof that the Kasami code is completely regular. The automorphism groups of the Kasami code and the related q-ary MDS code are determined. New cyclic completely regular codes over finite fields a power of 2, generalized Kasami codes, are constructed;they have coset graphs isomorphic to that of the Kasami codes. Another wide class of completely regular codes, including additive codes, as well as unrestricted codes, is obtained by combining cosets of the Kasami or generalized Kasami *** Codes 05E30, 94B05 Copyright © 2018, The Authors. All rights reserved.

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Multi-Layer Visual Perception for No-Reference Image Quality Assessment

Multi-Layer Visual Perception for No-Reference Image Quality...

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IEEE International Conference on Electronic Information and Communication Technology (ICEICT)

作者： Junwei Qi Yingzhen Wang Qingchun Wang Yingsong Li College of Computer Science and Technology Harbin Engineering University Harbin China College of Information and Communication Engineering Harbin Engineering University Harbin China Shanghai Yanding Information Technology Co. Ltd. Shanghai China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei Anhui China

In this work, we propose a no-reference image quality evaluation approach, aiming to solve the problem that the traditional convolutional neural network is insufficient to express the global information of the image. Therefore, in order to make the captured image features have the coherence of global context information, we combine a Transformer structure widely used in NLP (natural language processing) with the traditional CNN to realize the attention mechanism in the human visual perception characteristics. Firstly, the self-attention mechanism of Transformer is used to learn the global representation of the image from the multi-layer features extracted from different levels of CNN. Additionally, to forecast the ultimate image quality score, the global and local attributes are combined. Finally, the proposed algorithm is evaluated on three public datasets commonly used in CSIQ [1], TID2013 [2] and LIVE [3]. Compared with eight traditional no-reference image quality evaluation algorithms and five methods based on deep learning, the proposed algorithm achieves competitive results.

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Study of Robust Direction Finding Based on Joint Sparse Representation

arXiv

引用

arXiv 2024年

作者： Li, Yingsong Xiao, Wudang Zhao, Luyu Huang, Zhixiang Li, Qiang Li, Liping de Lamare, Rodrigo C. The Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Anhui Hefei230601 China PUC-Rio Brazil The University of York United Kingdom Gávea 22451-900 Brazil The Department of Electronic Engineering University of York YorkYO10 5DD United Kingdom

Standard Direction of Arrival (DOA) estimation methods are typically derived based on the Gaussian noise assumption, making them highly sensitive to outliers. Therefore, in the presence of impulsive noise, the performance of these methods may significantly deteriorate. In this paper, we model impulsive noise as Gaussian noise mixed with sparse outliers. By exploiting their statistical differences, we propose a novel DOA estimation method based on sparse signal recovery (SSR). Furthermore, to address the issue of grid mismatch, we utilize an alternating optimization approach that relies on the estimated outlier matrix and the on-grid DOA estimates to obtain the off-grid DOA estimates. Simulation results demonstrate that the proposed method exhibits robustness against large outliers. Copyright © 2024, The Authors. All rights reserved.

关键词： Impulse noise

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Triorthogonal Codes and Self-dual Codes

arXiv

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arXiv 2024年

作者： Shi, Minjia Lu, Haodong Kim, Jon-Lark Solé, Patrick The Key Laboratory of Intelligent Computing Signal Processing Ministry of Education School of Mathematical Sciences Anhui University Hefei230601 China State Key Laboratory of Integrated Service Networks Xidian University Xi’an710071 China Department of Mathematics Sogang University Seoul Korea Republic of Aix Marseille Univ CNRS Centrale Marseille I2M Marseille France

Triorthogonal matrices were introduced in Quantum Information Theory in connection with distillation of magic states (Bravyi and Haah (2012)). We give an algorithm to construct binary triorthogonal matrices from binary self-dual codes. Further, we generalize to this setting the classical coding techniques of shortening and extending. We also give some simple propagation *** Codes 94B05 © 2024, CC BY.

关键词： Matrix algebra

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VANER: Leveraging Large Language Model for Versatile and Adaptive Biomedical Named Entity Recognition 27

VANER: Leveraging Large Language Model for Versatile and Ada...

引用

27th European Conference on Artificial Intelligence, ECAI 2024

作者： Bian, Junyi Zhai, Weiqi Huang, Xiaodi Zheng, Jiaxuan Zhu, Shanfeng School of Computer Science Fudan University Shanghai200433 China Institute of Science and Technology for Brain-Inspired Intelligence Fudan University China Ministry of Education Shanghai200433 China MOE Frontiers Center for Brain Science Fudan University Shanghai200433 China Zhangjiang Fudan International Innovation Center Shanghai200433 China Shanghai Key Lab of Intelligent Information Processing Fudan University Shanghai200433 China School of Computing and Mathematics Charles Sturt University AlburyNSW2640 Australia

ISBN: (纸本)9781643685489

The prevalent solution for BioNER involves using representation learning techniques combined with sequence ***, such methods are inherently task-specific, demonstrate poor generalizability, and often require a dedicated model for each *** leverage the versatile capabilities of recent large language models (LLMs), several approaches have explored generative techniques for entity ***, these approaches often fall short compared to previous sequence labeling *** this paper, we utilize the open-sourced LLM LLaMA2 as the backbone model, and design specific instructions to distinguish between different types of entities and *** combining the LLM's understanding of instructions with sequence labeling techniques, we train a model using a mix of datasets capable of extracting various types of *** that the backbone LLMs lacks specialized medical knowledge, we also integrate external entity knowledge bases and employ instruction tuning to enable the model to densely recognize curated *** parameter-efficient training model, VANER, significantly outperforms previous LLMs-based *** the first time, as an LLM-based model, VANER surpasses the majority of conventional state-of-the-art BioNER systems, achieving the highest F1 scores across three datasets. © 2024 The Authors.

关键词： labeled data

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ONE2SET + Large Language Model: Best Partners for keyphrase Generation

arXiv

引用

arXiv 2024年

作者： Shao, Liangying Zhang, Liang Peng, Minlong Ma, Guoqi Yue, Hao Sun, Mingming Su, Jinsong School of Informatics Xiamen University China Key Laboratory of Digital Protection and Intelligent Processing of Intangible Cultural Heritage of Fujian and Taiwan Xiamen University Ministry of Culture and Tourism China Cognitive Computing Lab Baidu Research China Beijing Institute of Mathematical Sciences and Applications China

keyphrase generation (KPG) aims to automatically generate a collection of phrases representing the core concepts of a given document. The dominant paradigms in KPG include ONE2SEQ and ONE2SET. Recently, there has been increasing interest in applying large language models (LLMs) to KPG. Our preliminary experiments reveal that it is challenging for a single model to excel in both recall and precision. Further analysis shows that: 1) the ONE2SET paradigm owns the advantage of high recall, but suffers from improper assignments of supervision signals during training;2) LLMs are powerful in keyphrase selection, but existing selection methods often make redundant selections. Given these observations, we introduce a generate-then-select framework decomposing KPG into two steps, where we adopt a ONE2SET-based model as generator to produce candidates and then use an LLM as selector to select keyphrases from these candidates. Particularly, we make two important improvements on our generator and selector: 1) we design an Optimal Transport-based assignment strategy to address the above improper assignments;2) we model the keyphrase selection as a sequence labeling task to alleviate redundant selections. Experimental results on multiple benchmark datasets show that our framework significantly surpasses state-ofthe- art models, especially in absent keyphrase prediction. We release our code at https: //***/DeepLearnXMU/KPG-SetLLM. Copyright © 2024, The Authors. All rights reserved.

关键词： Modeling languages

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