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17th IEEE International Conference on Mechatronics and Automation, ICMA 2020

作者： Wang, Xiaofei Chen, Chenfei Li, Zhaotong Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin300384 China

ISBN: (纸本)9781728164151

Augmented reality (AR) technology is a cutting technology. It can enhance the perception of reality and provide more information of the real world. AR technology is used in many fields, like medical, industry, and education. In this paper, AR is introduced into engineering drawing course. Engineering drawing course is difficult to learn as it is a knowledge that students rarely contact with. To have a close contact with the models and the views, a convenient AR application (AR app) is proposed in the paper. With the help of the AR app, virtual models and real views are combined well. The models can be moved and rotated by touching the screen. Some videos of model assembly and disassembly can be obtained when scanning the quick response code (QR code). Thus, it is convenient for students to use mobile phone to study engineering drawing effectively. The interactive teaching environment enhances students' spatial thinking and cultivates their sense of innovation. © 2020 IEEE.

关键词： Augmented reality

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Analysis of Anchor-Based and Anchor-Free Object Detection Methods Based on Deep Learning 17

Analysis of Anchor-Based and Anchor-Free Object Detection Me...

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17th IEEE International Conference on Mechatronics and Automation, ICMA 2020

作者： Liu, Shujian Zhou, Haibo Li, Chenming Wang, Shuo Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin300384 China

ISBN: (纸本)9781728164151

As one of the core mission of computer vision, object detection has been widely applied with the rapid development of computer technology, especially in the fields of face detection, behavior detection, auto driving, and intelligent monitoring. Aiming at the shortcomings of the traditional object detection, such as low detection accuracy, low efficiency and poor robustness, this article summarizes deep learning-based detectors of two kinds of modules: Anchor-Based and Anchor-Free. The performance of each detector is compared and analyzed in this paper as well. In addition, we summarize the development of object detection's key technologies from the aspect of improvement of Backbone, the optimization of NMS, imbalance of positive and negative samples' solution etc. Finally, the development trend of object detection is discussed from the prospect of lightweight detection model, weakly supervision detection and small object detection etc. © 2020 IEEE.

关键词： Object detection

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MEVTR: A Multilingual Model Enhanced With Visual Text Representations 30

MEVTR: A Multilingual Model Enhanced With Visual Text Repres...

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Wang, Xiaohua Fei, Wenlong Hu, Min Zhang, Qingyu Zhu, Aoqiang School of Computer Science and Information Engineering HeFei University of Technology China Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine China

ISBN: (纸本)9782493814104

The goal of multilingual modelling is to generate multilingual text representations for various downstream tasks in different languages. However, some state-of-the-art pre-trained multilingual models perform poorly on many low-resource languages due to the lack of representation space and model capacity. To alleviate this issue, we propose a Multilingual model Enhanced with Visual Text Representations (MEVTR), which complements textual representations and extends the multilingual representation space with visual text representations. First, the visual encoder focuses on the glyphs and structure of the text to obtain visual text representations, and the textual encoder obtains textual representations. Then, multilingual representations are enhanced by aligning and fusing visual text representations and textual representations. Moreover, we propose similarity constraint, a self-supervised task to prompt the visual encoder to focus on more additional information. Prefix alignment and multi-head bilinear module are designed to acquire an improved integration effect of visual text representations and textual representations. Experimental results indicate that MEVTR benefits from visual text representations and achieves significant performance gains in downstream tasks. In particular, in the zero-shot cross-lingual transfer task, MEVTR achieves results that outperform the state-of-the-art adapter-based framework without the target language adapter. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Signal encoding

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Time series clustering adaptive enhanced method for time-dependent reliability analysis and design optimization

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Computer Methods in Applied Mechanics and Engineering 2025年 443卷

作者： Dequan Zhang Ying Zhao Meide Yang Chao Jiang Xu Han Qing Li State Key Laboratory of Intelligent Power Distribution Equipment and System School of Mechanical Engineering Hebei University of Technology Tianjin 300401 PR China State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle College of Mechanical and Vehicle Engineering Hunan University Changsha 410082 PR China School of Aerospace Mechanical and Mechatronic Engineering The University of Sydney Sydney 2006 New South Wales Australia

Adaptive Kriging model has gained growing attention for its effectiveness in reducing the computational costs in time-dependent reliability analysis (TRA). However, the existing methods struggle to identify critical sample regions, leverage parallel computational resources, and assess the value for sample trajectories, thus restricting improvement in accuracy and efficiency. To address the challenges, this study proposes a time series clustering adaptive enhanced method (TSCM). TSCM first employs the time series clustering technique to partition the sample region efficiently. A novel time-dependent Kriging occurrence learning function is then introduced to account for both the uncertainty of sample trajectories and its influence on the approximated limit state boundary. Subsequently, an adaptive sampling strategy is developed to select training samples in parallel, guided by an uncertainty-based assessment of sample regions. After that, a time-dependent error-based stopping criterion is introduced to determine the training stage and terminate the update process. Finally, TSCM is extended to time-dependent reliability-based design optimization problems. Several numerical examples and an engineering case study demonstrate the superior computational efficiency and accuracy of the proposed method.

关键词： Time-to-failure

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A stratified image-hiding method based on chaos

A stratified image-hiding method based on chaos

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International Conference on Bio-Inspired computing: Theories and Applications, BICTA

作者： Ying Li Qiang Zhang Na Ma Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian China

This paper presents a stratified image hiding scheme based on chaotic algorithm. In the pretreatment process chaotic sequences are used to encrypt the secret image. The histogram of the processed image is similar to that of white noise. A stratified secret data embedding thought is adopted in the embedding process. As the experimental results show, this algorithm has relatively large embedding capacity, good invisibility and robustness.

关键词： Cryptography Algorithm design and analysis Discrete wavelet transforms PSNR Pixel

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DNA computing-based cryptography

DNA computing-based cryptography

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International Conference on Bio-Inspired computing: Theories and Applications, BICTA

作者： Xing Wang Qiang Zhang Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian China

DNA computing theories can be applied in cryptography and it is a very hopeful direction. Though still in primitive level, it applies in many fields and solved some hard problems successfully. The art of cryptography security is to make anybody can not read it by encoding message. This paper use a new way to show how cryptography works with DNA computing, it can transmit message securely and effectively. The RSA algorithm belongs to asymmetric key cryptography, it is used in this paper connecting with DNA computing technique to encrypt message.

关键词： DNA computing Cryptography Encoding Arithmetic Turing machines Chemicals Art Security Computational modeling Qualifications

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A multilevel image encryption algorithm based on chaos and DNA coding

A multilevel image encryption algorithm based on chaos and D...

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International Conference on Bio-Inspired computing: Theories and Applications, BICTA

作者： Qian Wang Qiang Zhang Changjun Zhou Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian China

Chaos has been attracted much attention in current research of image encryption. In this paper, we change the location of pixels and pixel values through the combination of chaos with DNA coding. First of all, we transform the digital image into DNA coding matrix based on DNA code rules. Secondly, we divided this matrix into four sub matrixes, and disorder these sub matrixes through logistic chaotic sequence. Then, we scramble the sub matrixes by adding new logistic chaotic sequences and get the new sub matrixes. Finally, we join all scrambled DNA sub-matrixes in a DNA sequence and decode the scramble DNA matrix to image matrix. The experiment results demonstrate that the proposed scheme is effective, and it has wide secret key space, strong sensibility, high security and good ability of resisting statistic attack.

关键词： Cryptography Chaos DNA Image coding Sequences Logistics Digital images Decoding Security Statistics

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GP-Net: Global Perceptual Network with Adaptive Gradient Clipping for Emotional Image Classification 8

GP-Net: Global Perceptual Network with Adaptive Gradient Cli...

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8th International Conference on intelligent computing and Signal Processing, ICSP 2023

作者： Wang, Xiaohua Yang, Jie Hu, Min Wu, Xia Hefei University of Technology Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer Science and Information Engineering Hefei China

ISBN: (纸本)9798350302455

Traditional image emotion recognition focuses only on the emotion information embedded in the subject or part of the image, while ignoring the global emotion information. In this paper, we propose a new network based on Vision Transformer: a global perception network, containing a main module and a background module. The main module enhances the weighting of objects by showing the interdependencies between modelled channels. The background module further searches for emotional information in the background. In addition, we employ multi-task learning and Adaptive Gradient Clipping to improve the network. Extensive experiments show that our proposed method outperforms the state-of-the-art methods for image sentiment analysis. © 2023 IEEE.

关键词： Image classification

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Cross-Stage Mutual Distillation for Replay Attack Detection

Cross-Stage Mutual Distillation for Replay Attack Detection

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6th International Conference on intelligent computing and Signal Processing (ICSP)

作者： Yinqing Cheng Lasheng Zhao Ling Wang Han Wang Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian China

ISBN: (数字)9798350376548

ISBN: (纸本)9798350376555

Automated speaker verification systems face a higher risk of replay attacks in practice. However, the existing studies face the problem of limited detection capabilities and insufficient use of shallow fine-grained information. To address these issues, we propose the cross-stage mutual distillation(CS-MD) framework, which involves two models learning from a deep network output of each other in different stages of training. This mutual learning approach enhances the ability of shallow networks to capture fine-grained speech information. Additionally, we use an attentional feature fusion module to integrate shallow information more effectively. The multi-scale attention mechanisms in this module can combine local and global speech features while preserving detailed information. Experimental results on the ASVspoof 2019 physical access dataset demonstrate that our proposed method outperforms state-of-the-art methods in terms of EER and min t-DCF metrics, validating the effectiveness of our CS-MD framework.

关键词： Training Voice activity detection Measurement Knowledge engineering Attention mechanisms Speech enhancement Signal processing Feature extraction Faces

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Image encryption algorithm based on DNA biological properties and chaotic systems

Image encryption algorithm based on DNA biological propertie...

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International Conference on Bio-Inspired computing: Theories and Applications, BICTA

作者： Qian Wang Qiang Zhang Xiaopeng Wei Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian university Dalian China

With the rapid development of DNA computing, people began to use DNA technology to encrypt information. In this paper, we combine the biological characteristics of DNA and the improved sequence of Logistic mapping method, encrypt the image. The biological characteristics of DNA can better scramble image pixel, and the improved sequence can better change the pixel values. The encryption effect of this paper is better than traditional encryption, and the correlation of adjacent pixels is very low.

关键词： Biomedical imaging Cryptography Clocks Biology

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