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Image inpainting via Smooth Tucker decomposition and Low-rank Hankel constraint

International Journal of Computers and Applications 2023年第6期45卷 421-432页

作者： Cai, Jing Jiang, Jiawei Wang, Yibing Zheng, Jianwei Xu, Honghui Department of Forensic Science Zhejiang Police College Hangzhou China Key Laboratory of Public Security Information Application Based on Big-Data Architecture Hangzhou China College of Computer Science and Technology Zhejiang University of Technology Hangzhou China

Image inpainting, aiming at exactly recovering missing pixels from partially observed entries, is typically an ill-posed problem. As a powerful constraint, low-rank priors have been widely applied in image inpainting to transform such problems into well-posed ones. However, the low-rank assumption of original visual data is only in an approximate mode, which in turn results in suboptimal recovery of fine-grained details, particularly when the missing rate is extremely high. Moreover, a single prior cannot faithfully capture the complex texture structure of an image. In this paper, we propose a joint usage of Smooth Tucker decomposition and Low-rank Hankel constraint (STLH) for image inpainting, which enables simultaneous capturing of the global low-rankness and local piecewise smoothness. Specifically, based on the Hankelization operation, the original image is mapped to a high-order structure for capturing more spatial and spectral information. By employing Tucker decomposition for optimizing the Hankel tensor and simultaneously applying Discrete Total Variation (DTV) to the Tucker factors, sharper edges are generated and better isotropic properties are enhanced. Moreover, to approximate the essential rank of the Tucker decomposition and avoid facing the uncertainty problem of the upper-rank limit, a reverse strategy is adopted to approximate the true rank of the Tucker decomposition. Finally, the overall image inpainting model is optimized by the well-known alternate least squares (ALS) algorithm. Extensive experiments show that the proposed method achieves state-of-the-art performance both quantitatively and qualitatively. Particularly, in the extreme case with 99% pixels missed, the results from STLH are averagely ahead of others at least 0.9dB in terms of PSNR values. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Pixels

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Predicting visual acuity with machine learning in treated ocular trauma patients

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International Journal of Ophthalmology(English edition) 2023年第7期16卷 1005-1014页

作者： Zhi-Lu Zhou Yi-Fei Yan Jie-Min Chen Rui-Jue Liu Xiao-Ying Yu Meng Wang Hong-Xia Hao Dong-Mei Liu Qi Zhang Jie Wang Wen-Tao Xia Department of Forensic Medicine Guizhou Medical UniversityGuiyang 550009Guizhou ProvinceChina Shanghai Key Laboratory of Forensic Medicine Shanghai Forensic Service PlatformInstitute of Forensic ScienceMinistry of JusticeShanghai 200063China The SMART(Smart Medicine and AI-based Radiology Technology)Lab Shanghai Institute for Advanced Communication and Data ScienceShanghai UniversityShanghai 200444China School of Communication and Information Engineering Shanghai UniversityShanghai 200444China Basic Medical College Jiamusi UniversityJiamusi 154007Heilongjiang ProvinceChina

AIM:To predict best-corrected visual acuity(BCVA)by machine learning in patients with ocular trauma who were treated for at least ***:The internal dataset consisted of 850 patients with 1589 eyes and an average age of *** initial visual acuity was 0.99 log *** test dataset consisted of 60 patients with 100 eyes collected while the model was *** different machine-learning algorithms(Extreme Gradient Boosting,support vector regression,Bayesian ridge,and random forest regressor)were used to predict BCVA,and four algorithms(Extreme Gradient Boosting,support vector machine,logistic regression,and random forest classifier)were used to classify BCVA in patients with ocular trauma after treatment for 6mo or *** features were obtained from outpatient records,and ocular parameters were extracted from optical coherence tomography images and fundus *** features were put into different machine-learning models,and the obtained predicted values were compared with the actual BCVA *** best-performing model and the best variable selected were further evaluated in the test ***:There was a significant correlation between the predicted and actual values[all Pearson correlation coefficient(PCC)>0.6].Considering only the data from the traumatic group(group A)into account,the lowest mean absolute error(MAE)and root mean square error(RMSE)were 0.30 and 0.40 log MAR,*** the traumatic and healthy groups(group B),the lowest MAE and RMSE were 0.20 and 0.33 log MAR,*** sensitivity was always higher than the specificity in group A,in contrast to the results in group *** classification accuracy and precision were above 0.80 in both *** MAE,RMSE,and PCC of the test dataset were 0.20,0.29,and 0.96,*** sensitivity,precision,specificity,and accuracy of the test dataset were 0.83,0.92,0.95,and 0.90,***:Predicting BCVA using machine-learning models in patients wit

关键词： ocular trauma predicting visiual acuity best-corrected visual acuity visual dysfunction machine learning

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Fine-scale north-to-south genetic admixture profile in Shaanxi Han Chinese revealed by genome-wide demographic history reconstruction

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植物分类学报 2022年第4期60卷 955-972页

作者： Guang-Lin He Meng-Ge Wang Ying-Xiang Li Xing Zou Hui-Yuan Yeh Ren-Kuan Tang Xiao-Min Yang Zheng Wang Jian-Xin Guo Ting Luo Jing Zhao Jin Sun Rong Hu Lan-Hai Wei Gang Chen Yi-Ping Hou Chuan-Chao Wang Department of Anthropology and Ethnology Institute of AnthropologyNational Institute for Data Science in Health and MedicineState Key Laboratory of Marine Environmental ScienceState Key Laboratory of Cellular Stress Biologyand School of Life SciencesXiamen UniversityXiamen 361005China Institute of Forensic Medicine West China School of Basic Science and Forensic MedicineSichuan UniversityChengdu 610065China Institute of Forensic Medicine West China School of Basic Science and Forensic MedicineSichuan UniversityChengdu 610065China Department of Anthropology and Ethnology Institute of AnthropologyNational Institute for Data Science in Health and MedicineState Key Laboratory of Marine Environmental ScienceState Key Laboratory of Cellular Stress Biologyand School of Life SciencesXiamen UniversityXiamen 361005China School of Humanities Nanyang Technological UniversityNanyang 639798Singapore Department of Forensic Medicine College of Basic MedicineChongqing Medical UniversityChongqing 400331China Hunan Key Laboratory of Bioinformatics School of Computer Science and EngineeringCentral South UniversityChangsha 410075China

The Han Chinese are the world's largest ethnic group residing across *** province in northern China was a pastoral-agricultural interlacing region sensitive to climate change since Neolithic times,which makes it a vital place for studying population ***,genetic studies of Shaanxi Han are underrepresented due to the lack of high-density sampling and genome-wide ***,we genotyped 700 000 single nucleotide polymorphisms(SNPs)in 200 Han individuals from nine populations in Shaanxi and compared with available modem and ancient Eurasian *** revealed a north-south genetic cline in Han Chinese with Shaanxi Han locating at the northern side of the *** detected the western Eurasian-related admixture in Shaanxi populations,especially in Guanzhong and Shanbei Han Chinese in proportions of 2％-4.6％.Shaanxi Han were suggested to derive a large part of ancestry(39％-69％)from a lineage that also contributed largely to ancient and present-day Tibetans(85％)as well as southern Han,supporting the common northern China origin of modem Sino-Tibetan-speaking populations and southwestward expansion of millet farmers from the middle-upper Yellow River Basin to the Tibetan Plateau and to southern *** rest of the ancestry of Shaanxi Han was from a lineage closely related to ancient and present-day Austronesian and Tai-Kadai speaking populations in southern China and Southeast *** also observed a genetic substructure in Shaanxi Han in terms of north-south-related ancestry corresponding well to the *** mitochondrial DNA and paternal Y-chromosome lineages further demonstrated the aforementioned admixture pattern of Han Chinese in Shaanxi province.

关键词： ancestral makeup genetic relationship haplogroup Northern Han population substructure western Eurasian admixture

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A method to convert traditional fingerprint ACE/ACE-V outputs ("identification", "inconclusive", "exclusion") to Bayes factors

arXiv

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arXiv 2024年

作者： Morrison, Geoffrey Stewart Forensic Data Science Laboratory Aston University Birmingham United Kingdom Forensic Evaluation Ltd. Birmingham United Kingdom

Fingerprint examiners appear to be reluctant to adopt probabilistic reasoning, statistical models, and empirical validation. The rate of adoption of the likelihood-ratio framework by fingerprint practitioners appears to be near zero. A factor in the reluctance to adopt the likelihood-ratio framework may be a perception that it would require a radical change in practice. The present paper proposes a small step that would require minimal changes to current practice. It proposes and demonstrates a method to convert traditional fingerprint-examination outputs ("identification", "inconclusive", and "exclusion") to well-calibrated Bayes factors. The method makes use of a beta-binomial model, and both uninformative and informative priors. © 2024, CC BY-NC-SA.

关键词： Palmprint recognition

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Resampling Factor Estimation via Dual-Stream Convolutional Neural Network

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Computers, Materials & Continua 2021年第1期66卷 647-657页

作者： Shangjun Luo Junwei Luo Wei Lu Yanmei Fang Jinhua Zeng Shaopei Shi Yue Zhang School of Data and Computer Science Guangdong Province Key Laboratory of Information Security TechnologyMinistry of Education Key Laboratory of Machine Intelligence and Advanced ComputingSun Yat-sen UniversityGuangzhou510006China Academy of Forensic Science Shanghai200063China College of Information Science and Technology Jinan UniversityGuangzhou510632China Department of Computer Science University of Massachusetts LowellLowellMA 01854USA

The estimation of image resampling factors is an important problem in image *** all the resampling factor estimation methods,spectrumbased methods are one of the most widely used methods and have attracted a lot of research ***,because of inherent ambiguity,spectrum-based methods fail to discriminate upscale and downscale operations without any prior *** general,the application of resampling leaves detectable traces in both spatial domain and frequency domain of a resampled ***,the resampling process will introduce correlations between neighboring *** this case,a set of periodic pixels that are correlated to their neighbors can be found in a resampled ***,the resampled image has distinct and strong peaks on spectrum while the spectrum of original image has no clear ***,in this paper,we propose a dual-stream convolutional neural network for image resampling factors *** of the two streams is gray stream whose purpose is to extract resampling traces features directly from the rescaled *** other is frequency stream that discovers the differences of spectrum between rescaled and original *** features from two streams are then fused to construct a feature representation including the resampling traces left in spatial and frequency domain,which is later fed into softmax layer for resampling factor *** results show that the proposed method is effective on resampling factor estimation and outperforms some CNN-based methods.

关键词： Image forensics image resampling detection parameter estimation convolutional neural network

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Revolutionizing the Life sciences by Developing a Holographic Digital Mannequin

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Engineering 2023年第8期27卷 14-17页

作者： Bin Cong Xin-An Liu Shiming Zhang Zhiyu Ni Liping Wang Hebei Key Laboratory of Forensic Medicine College of Forensic MedicineHebei Medical UniversityShijiazhuang 050017China College of Integrated Traditional Chinese and Western Medicine Hebei Medical UniversityShijiazhuang 050017China CAS Key Laboratory of Brain Connectome and Manipulation Shenzhen–Hong Kong Institute of Brain ScienceShenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China Institute of Data Intelligence Bigmath(Shenzhen)Technology Co.Ltd.Shenzhen 518063China School of Basic Medical Sciences Hebei UniversityBaoding 071000China Guangdong Provincial Key Laboratory of Brain Connectome and Behavior the Brain Cognition and Brain Disease InstituteShenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China Research Unit of Digestive Tract Microecosystem Pharmacology and Toxicology Chinese Academy of Medical SciencesShijiazhuang 050017China

*** need to develop a holographic digital mannequin Life processes,including high intelligence,self-organization,and homeostasis,are characterized by the biological organism in the form of self-renewal,self-replication and self-regulation,metabolism,self-repair,and self-reproduction,which are all processes of multisystem coordinated movement[1].Research in the field of life sciences is not limited to the use of advanced observational methods to reveal microscopic structures at the subcellular or molecular *** based on these methods alone cannot characterize the dynamic processes of life at the microscopic and molecular level[2].

关键词： holographic coordinated multisystem

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Advancing a paradigm shift in evaluation of forensic evidence: The rise of forensic data science

Forensic Science International: Synergy

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forensic science International: Synergy 2022年 5卷 100270页

作者： Morrison, Geoffrey Stewart Forensic Data Science Laboratory Aston University UK Birmingham United Kingdom Forensic Evaluation Ltd UK Birmingham United Kingdom

Widespread practice across the majority of branches of forensic science uses analytical methods based on human perception, and interpretive methods based on subjective judgement. These methods are non-transparent and are susceptible to cognitive bias, interpretation is often logically flawed, and forensic-evaluation systems are often not empirically validated. I describe a paradigm shift in which existing methods are replaced by methods based on relevant data, quantitative measurements, and statistical models;methods that are transparent and reproducible, are intrinsically resistant to cognitive bias, use the logically correct framework for interpretation of evidence (the likelihood-ratio framework), and are empirically validated under casework conditions. © 2022 The Author

关键词： forensic data science forensic science Likelihood ratio Paradigm shift Validation

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In the context of forensic casework, are there meaningful metrics of the degree of calibration?

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forensic science International: Synergy 2021年 3卷 100157页

作者： Morrison, Geoffrey Stewart Forensic Data Science Laboratory & Forensic Speech Science Laboratory Computer Science Department & Aston Institute for Forensic Linguistics Aston University Birmingham United Kingdom Forensic Evaluation Ltd Birmingham United Kingdom

forensic-evaluation systems should output likelihood-ratio values that are well calibrated. If they do not, their output will be misleading. Unless a forensic-evaluation system is intrinsically well-calibrated, it should be calibrated using a parsimonious parametric model that is trained using calibration data. The system should then be tested using validation data. Metrics of degree of calibration that are based on the pool-adjacent-violators (PAV) algorithm recalibrate the likelihood-ratio values calculated from the validation data. The PAV algorithm overfits on the validation data because it is both trained and tested on the validation data, and because it is a non-parametric model with weak constraints. For already-calibrated systems, PAV-based ostensive metrics of degree of calibration do not actually measure degree of calibration;they measure sampling variability between the calibration data and the validation data, and overfitting on the validation data. Monte Carlo simulations are used to demonstrate that this is the case. We therefore argue that, in the context of casework, PAV-based metrics are not meaningful metrics of degree of calibration;however, we also argue that, in the context of casework, a metric of degree of calibration is not required. © 2021

关键词： Calibration forensic inference and statistics Likelihood ratio Metric

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Vacuous standards – Subversion of the OSAC standards-development process

Forensic Science International: Synergy

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forensic science International: Synergy 2020年 2卷 206-209页

作者： Morrison, Geoffrey Stewart Neumann, Cedric Geoghegan, Patrick Henry Forensic Data Science Laboratory Computer Science Department Aston University Birmingham United Kingdom Forensic Speech Science Laboratory Aston Institute for Forensic Linguistics Aston University Birmingham United Kingdom Department of Mathematics & Statistics South Dakota State University Brookings SD United States Department of Biomedical Engineering Aston University Birmingham United Kingdom

In the context of development of standards for forensic science, particularly standards initially developed by the U.S. Organization of Scientific Area Committees for forensic science (OSAC), this perspective paper raises concern about the publication of vacuous standards. Vacuous standards generally state few requirements;the requirements they do state are often vague;compliance with their stated requirements can be achieved with little effort – the bar is set very low;and compliance with their stated requirements would not be sufficient to lead to scientifically valid results. This perspective paper proposes a number of requirements that we believe would be essential in order for a standard on validation of forensic-science methods to be fit for purpose. © 2020 The Authors

关键词： forensic science Method validation OSAC Standard Validation

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forensic comparison of fired cartridge cases: Feature-extraction methods for feature-based calculation of likelihood ratios

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forensic science International: Synergy 2022年 5卷 100272页

作者： Basu, Nabanita Bolton-King, Rachel S. Morrison, Geoffrey Stewart Forensic Data Science Laboratory Aston University Birmingham United Kingdom School of Justice Security & Sustainability Department of Society Crime & Environment Staffordshire University Stoke-on-Trent United Kingdom Forensic Evaluation Ltd Birmingham United Kingdom

We describe and validate a feature-based system for calculation of likelihood ratios from 3D digital images of fired cartridge cases. The system includes a database of 3D digital images of the bases of 10 cartridges fired per firearm from approximately 300 firearms of the same class (semi-automatic pistols that fire 9 mm diameter centre-fire Luger-type ammunition, and that have hemispherical firing pins and parallel breech-face marks). The images were captured using Evofinder®, an imaging system that is commonly used by operational forensic laboratories. A key component of the research reported is the comparison of different feature-extraction methods. Feature sets compared include those previously proposed in the literature, plus Zernike-moment based features. Comparisons are also made of using feature sets extracted from the firing-pin impression, from the breech-face region, and from the whole region of interest (firing-pin impression + breech-face region + flowback if present). Likelihood ratios are calculated using a statistical modelling pipeline that is standard in forensic voice comparison. Validation is conducted and results are assessed using validation procedures and validation metrics and graphics that are standard in forensic voice comparison. © 2022

关键词： Calibration Cartridge case Feature Firearm Likelihood ratio Validation

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