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2024 International conference on Computer Graphics, Artificial Intelligence, and Data processing, ICCAID 2024

作者： Liao, Fengxiang Leng, Lu Guo, Guodong Jiangxi Provincial Key Laboratory of Image Processing and Pattern Recognition Nanchang Hangkong University Nanchang 330063 China Ningbo Institute of Digital Twin Eastern Institute of Technology Ningbo 315000 China

ISBN: (纸本)9781510689275

Biometric systems, even with high accuracies, commonly suffer from various attacks. In practical applications, some systems directly display the matching scores, or attackers can obtain the matching scores. This paper proposes a novel matching-score-based template reconstruction attack, which reveals that matching scores can leak the spatial neighborhood range of the attacked template, resulting in some potential security and privacy risks. The dissimilarity (matching score) between two real-number templates is measured by the Euclidean distance. A small number of match scores can be obtained by matching the attacked template with a few randomly selected or generated fake templates. An equation set can be established based on the formulae of the matching scores. However, it is difficult to directly solve the quadratic equation set. We skillfully simplify the quadratic equation set into a linear equation set, which obviously reduces the complexity, especially for large-size templates. This novel attack can be extended to other algorithms, and used to evaluate the security and privacy of the related algorithms. © 2025 SPIE.

关键词： biometric privacy biometric security matching score Template reconstruction attack

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Phase Retrieval Based on Enhanced Generator Conditional Generative Adversarial Network 4

Phase Retrieval Based on Enhanced Generator Conditional Gene...

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4th International conference on Intelligent Control, Measurement and Signal processing, ICMSP 2022

作者： Pu, Shasha Li, Lan xiang, Yu Qiu, xiaolong School of Science Xi'an Shiyou University Xian710065 China

ISBN: (数字)9781665486583

ISBN: (纸本)9781665486583

Phase retrieval refers to the recovery of the original image using only the Fourier amplitude of the image. Due to the small amount of information contained in the Fourier amplitude, the common network structure cannot achieve accurate reconstruction of the image when the oversampling rate of the image is low. It is the key issue of phase retrieval to improve the structure of the neural network. We propose an application of end-to-end adversarial network to solve phase retrieval problems by adding a U-Net model to the conditional generative adversarial network(U-NetCGAN). This desired approach realizes multi-scale recognition and fusion of image features and improves the quality of image reconstruction. The experimental results show that the model is significantly better than the traditional phase retrieval algorithm. Compared to other algorithms, the evaluation indicators of PSNR and SSIM values in our approach have increased about 6 dB and 0.1, respectively. © 2022 IEEE.

关键词： Generative adversarial networks

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Deep Learning Enhanced Fluorescence Fluctuations Super-Resolution Microscopy 3

Deep Learning Enhanced Fluorescence Fluctuations Super-Resol...

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3rd conference on Biomedical Photonics and Cross-Fusion, BPC 2024

作者： Li, Yanru Liu, Lixin Wang, Lin School of Optoelectronic Engineering Xidian University Shaanxi Xi'an710071 China Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province College of Physics and Optoelectronic Engineering Shenzhen University Guangdong Shenzhen518060 China Central Laser Facility Research Complex at Harwell Science and Technology Facilities Council Rutherford Appleton Laboratory Harwell Didcot OxfordOX11 0QX United Kingdom

ISBN: (纸本)9781510682849

Fluorescence fluctuations super-resolution microscopy (FF-SRM) is a powerful tool in imaging and monitoring of biological subcellular structures and dynamics in cells. A variety of image reconstruction algorithms have been developed for FF-SRM. In order to obtain high spatiotemporal resolution, a U-Net-based deep learning method for super-resolution imaging of fluorescence fluctuations was developed. With just 20 frames, super-resolution images reconstructed using U-Net model could be comparable to those reconstructed using VeSRRF algorithm with several hundred frames, demonstrating its capability of advancing imaging capabilities. © 2024 SPIE

关键词： Fluorescence imaging

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Effective Tensor Completion via Element-Wise Weighted Low-Rank Tensor Train With Overlapping Ket Augmentation

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IEEE TRANSACTIONS ON CIRCUITS AND systems FOR VIDEO TECHNOLOGY 2022年第11期32卷 7286-7300页

作者： Zhang, Yang Wang, Yao Han, Zhi Chen, xi'ai Tang, Yandong Chinese Acad Sci Shenyang Inst Automat State Key Lab Robot Shenyang 110016 Peoples R China Chinese Acad Sci Shenyang Inst Automat Inst Robot & Intelligent Mfg Shenyang 110016 Peoples R China City Univ Hong Kong Dept Comp Sci Hong Kong Peoples R China Xi An Jiao Tong Univ Ctr Intelligent Decis Making & Machine Learning Sch Mangement Xian 710049 Peoples R China

Tensor completion methods based on the tensor train (TT) have the issues of inaccurate weight assignment and ineffective tensor augmentation pre-processing. In this work, we propose a novel tensor completion approach via the element-wise weighted technique. Accordingly, a novel formulation for tensor completion and an effective optimization algorithm, called tensor completion by parallel weighted matrix factorization via tensor train (TWMac-TT), is proposed. In addition, we specifically consider the recovery quality of edge elements from adjacent blocks. Different from traditional reshaping and ket augmentation, we utilize a new tensor augmentation technique called overlapping ket augmentation, which can further avoid blocking artifacts. We then conduct extensive performance evaluations on synthetic data and several real image data sets. Our experimental results demonstrate that the proposed algorithm TWMac-TT outperforms several other competing tensor completion methods. The code is available at https://***/yzcv/ TWMac-TT-OKA

关键词： Tensors Matrix decomposition Task analysis Automation Signal processing algorithms Optimization Mathematical models Tensor completion tensor train overlapping element-wise weighted ket augmentation

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Research on image Quality Assessment Methods for Weld Negatives 3

Research on Image Quality Assessment Methods for Weld Negati...

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3rd International conference on Digital Society and Intelligent systems, DSInS 2023

作者： Liu, Jiayue Wang, Lei Li, Mingfei Deng, Cong Luo, Weijian Li, Xufeng Lu, Shengzi Zhang, Ruida Chen, Junyang Dong, Shaohua Guangdong Institute of Special Equipment Inspection and Research Guangdong Province Guangzhou510000 China OIL&GAS Pipeline Research Center Beijing102200 China

ISBN: (纸本)9798350331387

para>Defects in pipeline welds are fatal for pipelines, considering that weld negatives need to be electronically preserved due to high preservation costs, easy damage, etc., and that most of the weld defects are judged with the help of intelligent computer recognition algorithms, the assessment of the quality of weld negatives after digitization is critical. At present, domestic and foreign research on the method of weld negative image quality assessment is still immature, especially after the processing of the image details is not clear, and the low quality of the image will directly affect the accuracy of the weld negative defect identification and determination. Therefore, this paper proposes a reference-free image quality assessment algorithm based on analytic sparse representation for this problem, which objectively evaluates the image quality of weld negatives, helps identify and judge weld defects, and has a vital practical role in guaranteeing the regular operation of pipelines. © 2023 IEEE.

关键词： Welds

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Now you see me, now you don't: an exploration of religious exnomination in DALL-E

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ETHICS AND INFORMATION TECHNOLOGY 2024年第2期26卷 27-27页

作者： Alfano, Mark Abedin, Ehsan Reimann, Ritsaart Ferreira, Marinus Cheong, Marc Macquarie Univ Dept Philosophy Sydney NSW Australia Univ Melbourne Sch Comp & Informat Syst Melbourne Vic Australia Flinders Univ S Australia Coll Business Govt & Law Adelaide SA Australia

Artificial intelligence (AI) systems are increasingly being used not only to classify and analyze but also to generate images and text. As recent work on the content produced by text and image Generative AIs has shown (e.g., Cheong et al., 2024, Acerbi & Stubbersfield, 2023), there is a risk that harms of representation and bias, already documented in prior AI and natural language processing (NLP) algorithms may also be present in generative models. These harms relate to protected categories such as gender, race, age, and religion. There are several kinds of harms of representation to consider in this context, including stereotyping, lack of recognition, denigration, under-representation, and many others (Crawford in Soundings 41:45-55, 2009;in: Barocas et al., SIGCIS conference, 2017). Whereas the bulk of researchers' attention thus far has been given to stereotyping and denigration, in this study we examine 'exnomination', as conceived by Roland Barthes (1972), of religious groups. Our case study is DALL-E, a tool that generates images from natural language prompts. Using DALL-E mini, we generate images from generic prompts such as "religious person." We then examine whether the generated images are recognizably members of a nominated group. Thus, we assess whether the generated images normalize some religions while neglecting others. We hypothesize that Christianity will be recognizably represented more frequently than other religious groups. Our results partially support this hypothesis but introduce further complexities, which we then explore.

关键词： Artificial intelligence Natural language processing Natural language generation DALL-E Exnomination

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Research on Kalman Filter Parallel Computing Method Based on OpenMP

Research on Kalman Filter Parallel Computing Method Based on...

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Electronic Materials and Information Engineering (EMIE), International conference on

作者： Panlong Sheng Pengju He Yimei Xu xiangmei Zhao School of Information Engineering Xi’an Eurasia University Xi’an China

ISBN: (数字)9798350390223

ISBN: (纸本)9798350390230

Kalman filtering is an algorithm widely used in state estimation of dynamic systems, and its wide applications include navigation, tracking and control systems. However, the computational complexity of Kalman filtering makes it inefficient when processing large-scale data. This paper studies the parallel processing method of Kalman filtering, and improves the execution efficiency of the algorithm by dividing the filtering process into blocks and parallelizing them. Through experiments on simulated data of sinusoidal signals plus Gaussian white noise, the significant advantages of parallel processing methods in computing time are verified, and the influence of block processing on filtering results is discussed.

关键词： Filtering Navigation Heuristic algorithms Signal processing algorithms Parallel processing White noise Signal processing

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2024 2nd International conference on Computer, Communication and Control, IC4 2024

2024 2nd International Conference on Computer, Communication...

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2nd International conference on Computer, Communication and Control, IC4 2024

ISBN: (纸本)9798350387933

The proceedings contain 134 papers. The topics discussed include: an adaptive storage switching algorithm for fault-tolerant network attached storage systems;Covid-19 prediction using machine learning algorithms;energy management of hybrid electric vehicles using cascaded fuzzy logic controller;dynamic lane management with IoT for real-time lane configuration and traffic flow;a closer look at sclera: emerging trends in biometric security;cognitive vision companion: an ai-enhanced support system for the visually impaired;advances in medical image processing for liver tumor recognition: a comprehensive survey;a gradient boosting algorithm to predict energy consumption for home applications;and review on text classification using improved deep learning models.

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Automated Bone Segmentation Using a Hybrid Model of DRLSE and Faster R-CNN 25

Automated Bone Segmentation Using a Hybrid Model of DRLSE an...

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25th IEEE conference on Signal processing - algorithms, Architectures, Arrangements, and Applications (IEEE SPA)

作者： Naderian, Amirkhashayar Sanei, Saeid Nottingham Trent Univ Dept Comp Sci Nottingham England

ISBN: (数字)9788362065424

ISBN: (纸本)9788362065424

The computer aided diagnosis systems from radiological images has been of interest to researchers mostly for detection of bone fracture or dislocation. The accuracy highly depends on bone segmentation. Any improvement of such systems, particularly for noisy X-ray images, is very valuable. Classical image segmentation depending on image homogeneity are time consuming and require pixel-wise labelling. On the other hand, saliency map based approaches fail to detect the region around the fracture or segment the dislocated bones. In our research we have used transfer learning to train the faster regional convolutional neural network (FCNN) alongside distance regularized level set evolution (DRLSE) to have accurate bone segmentation without any pixel-wise labelling enabling segmentation of the region around the fracture and dislocated bones. We applied the proposed method to a number of hand X-ray images and achieved accuracy values of 95% and average precision-recall of 0.96.

关键词： Bone segmentation distance regularized level set evolution Faster R-CNN image processing medical imaging transfer learning X-ray

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image processing for Knowledge and Comparison of Piranesi’s Carceri Editions 1

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3rd International and Interdisciplinary conference on image and Imagination, IMG 2021

作者： Menconero, Sofia Department of History Representation and Restoration of Architecture Sapienza University of Rome Piazza Borghese 9 Rome00186 Italy

ISBN: (数字)9783031259067

ISBN: (纸本)9783031259050

Piranesi printed the 16 etchings of the Carceri d’invenzione in 1761. This version, which is more widespread and better known, derives from the reworking of matrices that the Venetian engraver produced in 1749–50. These are the 14 plates of the Invenzioni capricciose di Carceri all’acquaforte. Many studies have focused on the semantic and formal comparison of the two main versions of the series. Up to now, comparisons have been conducted using juxtaposed pictures, whether original prints or digital reproductions. This procedure involves some limitations due to the effort of synthesis and mental superimposition of the two pictures of different editions to correctly identify the areas where changes occurred. The contribution proposes a method of formal comparison between the two main editions of the series through the digital superimposition of two states of the same plate so that it is easier, more immediate, and more accurate to note the changes. This method is based on the application of image processing algorithms, which let to obtain a synthesis picture in false colours that clearly shows the modified parts of each plate. Observation of the results has suggested the distinction of two main types of modifications carried out by Piranesi (additions/integrations and removal), clearly identifiable in the synthesis pictures. In addition to its implications for Piranesi studies, this research shows how digital image processing can be an essential tool for knowledge in the field of art. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Etching

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