Displaying publications 21 - 40 of 310 in total

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  1. Esmaeilzadeh P, Sambasivan M
    J Biomed Inform, 2016 12;64:74-86.
    PMID: 27645322 DOI: 10.1016/j.jbi.2016.09.011
    OBJECTIVES: Literature shows existence of barriers to Healthcare Information Exchange (HIE) assimilation process. A number of studies have considered assimilation of HIE as a whole phenomenon without regard to its multifaceted nature. Thus, the pattern of HIE assimilation in healthcare providers has not been clearly studied due to the effects of contingency factors on different assimilation phases. This study is aimed at defining HIE assimilation phases, recognizing assimilation pattern, and proposing a classification to highlight unique issues associated with HIE assimilation.

    METHODS: A literature review of existing studies related to HIE efforts from 2005 was undertaken. Four electronic research databases (PubMed, Web of Science, CINAHL, and Academic Search Premiere) were searched for articles addressing different phases of HIE assimilation process.

    RESULTS: Two hundred and fifty-four articles were initially selected. Out of 254, 44 studies met the inclusion criteria and were reviewed. The assimilation of HIE is a complicated and a multi-staged process. Our findings indicated that HIE assimilation process consisted of four main phases: initiation, organizational adoption decision, implementation and institutionalization. The data helped us recognize the assimilation pattern of HIE in healthcare organizations.

    CONCLUSIONS: The results provide useful theoretical implications for research by defining HIE assimilation pattern. The findings of the study also have practical implications for policy makers. The findings show the importance of raising national awareness of HIE potential benefits, financial incentive programs, use of standard guidelines, implementation of certified technology, technical assistance, training programs and trust between healthcare providers. The study highlights deficiencies in the current policy using the literature and identifies the "pattern" as an indication for a new policy approach.

    Matched MeSH terms: Databases, Factual*
  2. Ahmed A, Saeed F, Salim N, Abdo A
    J Cheminform, 2014;6:19.
    PMID: 24883114 DOI: 10.1186/1758-2946-6-19
    BACKGROUND: It is known that any individual similarity measure will not always give the best recall of active molecule structure for all types of activity classes. Recently, the effectiveness of ligand-based virtual screening approaches can be enhanced by using data fusion. Data fusion can be implemented using two different approaches: group fusion and similarity fusion. Similarity fusion involves searching using multiple similarity measures. The similarity scores, or ranking, for each similarity measure are combined to obtain the final ranking of the compounds in the database.

    RESULTS: The Condorcet fusion method was examined. This approach combines the outputs of similarity searches from eleven association and distance similarity coefficients, and then the winner measure for each class of molecules, based on Condorcet fusion, was chosen to be the best method of searching. The recall of retrieved active molecules at top 5% and significant test are used to evaluate our proposed method. The MDL drug data report (MDDR), maximum unbiased validation (MUV) and Directory of Useful Decoys (DUD) data sets were used for experiments and were represented by 2D fingerprints.

    CONCLUSIONS: Simulated virtual screening experiments with the standard two data sets show that the use of Condorcet fusion provides a very simple way of improving the ligand-based virtual screening, especially when the active molecules being sought have a lowest degree of structural heterogeneity. However, the effectiveness of the Condorcet fusion was increased slightly when structural sets of high diversity activities were being sought.

    Matched MeSH terms: Databases, Factual
  3. Arif SM, Holliday JD, Willett P
    J Chem Inf Model, 2010 Aug 23;50(8):1340-9.
    PMID: 20672867 DOI: 10.1021/ci1001235
    This paper discusses the weighting of two-dimensional fingerprints for similarity-based virtual screening, specifically the use of weights that assign greatest importance to the substructural fragments that occur least frequently in the database that is being screened. Virtual screening experiments using the MDL Drug Data Report and World of Molecular Bioactivity databases show that the use of such inverse frequency weighting schemes can result, in some circumstances, in marked increases in screening effectiveness when compared with the use of conventional, unweighted fingerprints. Analysis of the characteristics of the various schemes demonstrates that such weights are best used to weight the fingerprint of the reference structure in a similarity search, with the database structures' fingerprints unweighted. However, the increases in performance resulting from such weights are only observed with structurally homogeneous sets of active molecules; when the actives are diverse, the best results are obtained using conventional, unweighted fingerprints for both the reference structure and the database structures.
    Matched MeSH terms: Databases, Factual
  4. Hannan MA, Arebey M, Begum RA, Basri H, Al Mamun MA
    Waste Manag, 2016 Apr;50:10-9.
    PMID: 26868844 DOI: 10.1016/j.wasman.2016.01.046
    This paper presents a CBIR system to investigate the use of image retrieval with an extracted texture from the image of a bin to detect the bin level. Various similarity distances like Euclidean, Bhattacharyya, Chi-squared, Cosine, and EMD are used with the CBIR system for calculating and comparing the distance between a query image and the images in a database to obtain the highest performance. In this study, the performance metrics is based on two quantitative evaluation criteria. The first one is the average retrieval rate based on the precision-recall graph and the second is the use of F1 measure which is the weighted harmonic mean of precision and recall. In case of feature extraction, texture is used as an image feature for bin level detection system. Various experiments are conducted with different features extraction techniques like Gabor wavelet filter, gray level co-occurrence matrix (GLCM), and gray level aura matrix (GLAM) to identify the level of the bin and its surrounding area. Intensive tests are conducted among 250bin images to assess the accuracy of the proposed feature extraction techniques. The average retrieval rate is used to evaluate the performance of the retrieval system. The result shows that, the EMD distance achieved high accuracy and provides better performance than the other distances.
    Matched MeSH terms: Databases, Factual
  5. Zairina Ibrahim, Md Gapar Md Johar
    MyJurnal
    The process of software development life cycle (SDLC) is an important element of development phases to develop the application. In fact, there are needs to upgrade the sequence of methodology in software development. Thus, the SDLC is very crucial in order for them to ensure the quality of skills is placed accordingly in the workflow. This research contributes to the development of a new approach in system development workflow with the aim to properly manage system development projects. It started by providing some background data related to the previous mode of operation in the teamwork samples as shared by the stakeholders of the transformation projects and the new proposed Analysis System Development Framework (ASDF) method team members. Then, the key findings related to steps of software development such as (1) input for User Requirement Specification (URS) and (2) System Requirement Specification (SRS), (3) process for module, (4) process for database, (5) process for User Acceptance Testing (UAT) (6) output for Final Acceptance Testing (FAT) and empowerment for the whole level based on ASDF method. This paper contribution significantly to support the perception of high quality of skills in a teamwork, results in better performance of software development.
    Matched MeSH terms: Databases, Factual
  6. Ahmad P, Dummer PMH, Noorani TY, Asif JA
    Int Endod J, 2019 Jun;52(6):803-818.
    PMID: 30667524 DOI: 10.1111/iej.13083
    AIM: To analyse the main characteristics of the top 50 most-cited articles published in the International Endodontic Journal from 1967 to 2018.

    METHODOLOGY: The Clarivate Analytics' Web of Science 'All Databases', Elsevier's Scopus, Google Scholar and PubMed Central were searched to retrieve the 50 most-cited articles in the IEJ published from April 1967 to December 2018. The articles were analysed and information including number of citations, year of publication, contributing authors, institutions and countries, study design, study topic, impact factor and keywords was extracted.

    RESULTS: The number of citations of the 50 selected papers varied from 575 to 130 (Web of Science), 656 to164 (Elsevier's Scopus), 1354 to 199 (Google Scholar) and 123 to 3 (PubMed). The majority of papers were published in the year 2001 (n = 7). Amongst 102 authors, the greatest contribution was made by four contributors that included Gulabivala K (n = 4), Ng YL (n = 4), Pitt Ford TR (n = 4) and Wesselink PR (n = 4). The majority of papers originated from the United Kingdom (n = 8) with most contributions from King's College London Dental Institute (UK) and Eastman Dental Hospital, London. Reviews were the most common study design (n = 19) followed by Clinical Research (n = 16) and Basic Research (n = 15). The majority of topics covered by the most-cited articles were Outcome Studies (n = 9), Intracanal medicaments (n = 8), Endodontic microbiology (n = 7) and Canal instrumentation (n = 7). Amongst 76 unique keywords, Endodontics (n = 7), Mineral Trioxide Aggregate (MTA) (n = 7) and Root Canal Treatment (n = 7) were the most frequently used.

    CONCLUSION: This is the first study to identify and analyse the top 50 most-cited articles in a specific professional journal within Dentistry. The analysis has revealed information regarding the development of the IEJ over time as well as scientific progress in the field of Endodontology.

    Matched MeSH terms: Databases, Factual
  7. Agbolade O, Nazri A, Yaakob R, Ghani AAA, Cheah YK
    PeerJ Comput Sci, 2020;6:e249.
    PMID: 33816901 DOI: 10.7717/peerj-cs.249
    Over the years, neuroscientists and psychophysicists have been asking whether data acquisition for facial analysis should be performed holistically or with local feature analysis. This has led to various advanced methods of face recognition being proposed, and especially techniques using facial landmarks. The current facial landmark methods in 3D involve a mathematically complex and time-consuming workflow involving semi-landmark sliding tasks. This paper proposes a homologous multi-point warping for 3D facial landmarking, which is verified experimentally on each of the target objects in a given dataset using 500 landmarks (16 anatomical fixed points and 484 sliding semi-landmarks). This is achieved by building a template mesh as a reference object and applying this template to each of the targets in three datasets using an artificial deformation approach. The semi-landmarks are subjected to sliding along tangents to the curves or surfaces until the bending energy between a template and a target form is minimal. The results indicate that our method can be used to investigate shape variation for multiple datasets when implemented on three databases (Stirling, FRGC and Bosphorus).
    Matched MeSH terms: Databases, Factual
  8. Abdulhussain SH, Ramli AR, Saripan MI, Mahmmod BM, Al-Haddad SAR, Jassim WA
    Entropy (Basel), 2018 Mar 23;20(4).
    PMID: 33265305 DOI: 10.3390/e20040214
    The recent increase in the number of videos available in cyberspace is due to the availability of multimedia devices, highly developed communication technologies, and low-cost storage devices. These videos are simply stored in databases through text annotation. Content-based video browsing and retrieval are inefficient due to the method used to store videos in databases. Video databases are large in size and contain voluminous information, and these characteristics emphasize the need for automated video structure analyses. Shot boundary detection (SBD) is considered a substantial process of video browsing and retrieval. SBD aims to detect transition and their boundaries between consecutive shots; hence, shots with rich information are used in the content-based video indexing and retrieval. This paper presents a review of an extensive set for SBD approaches and their development. The advantages and disadvantages of each approach are comprehensively explored. The developed algorithms are discussed, and challenges and recommendations are presented.
    Matched MeSH terms: Databases, Factual
  9. MUHAMMAD IQBAL NORDIN, NOOR HAFHIZAH ABD RAHIM
    MyJurnal
    Parser is aprocess of classifying sentence structuresof a language. Parser receives a sentence and breaks it up into correct phrases. The purpose of this research is to develop a Malay single sentence parser that can help primary school studentsto learn Malay language according to the correct phrases. Thisis because research in Malay sentenceparsinghasnot gottenenough attention from researchers tothe extent ofbuildingparserprototypes. This research used top-down parsing technique,and grammar chosen was context-free grammar (CFG) for Malay language. However, to parse a sentence with correct phrase was a difficult task due to lack of resourcesfor obtainingMalay lexicon. Malay lexicon is a database that storesthousands of words with their correct phrases. Therefore, this research developeda Malay lexicon based on an articlefrom Dewan Masyarakatmagazine. In conclusion, this research can providehelpto the primaryschoolstudentsto organize correct Malay single sentences.
    Matched MeSH terms: Databases, Factual
  10. Arnia F, Oktiana M, Saddami K, Munadi K, Roslidar R, Pradhan B
    Sensors (Basel), 2021 Jul 04;21(13).
    PMID: 34283116 DOI: 10.3390/s21134575
    Facial recognition has a significant application for security, especially in surveillance technologies. In surveillance systems, recognizing faces captured far away from the camera under various lighting conditions, such as in the daytime and nighttime, is a challenging task. A system capable of recognizing face images in both daytime and nighttime and at various distances is called Cross-Spectral Cross Distance (CSCD) face recognition. In this paper, we proposed a phase-based CSCD face recognition approach. We employed Homomorphic filtering as photometric normalization and Band Limited Phase Only Correlation (BLPOC) for image matching. Different from the state-of-the-art methods, we directly utilized the phase component from an image, without the need for a feature extraction process. The experiment was conducted using the Long-Distance Heterogeneous Face Database (LDHF-DB). The proposed method was evaluated in three scenarios: (i) cross-spectral face verification at 1m, (ii) cross-spectral face verification at 60m, and (iii) cross-spectral face verification where the probe images (near-infrared (NIR) face images) were captured at 1m and the gallery data (face images) was captured at 60 m. The proposed CSCD method resulted in the best recognition performance among the CSCD baseline approaches, with an Equal Error Rate (EER) of 5.34% and a Genuine Acceptance Rate (GAR) of 93%.
    Matched MeSH terms: Databases, Factual
  11. Mohd Sani N, Aziz Z, Kamarulzaman A
    Ther Innov Regul Sci, 2021 05;55(3):490-502.
    PMID: 33231863 DOI: 10.1007/s43441-020-00243-y
    INTRODUCTION: Biosimilars are a cost-effective alternative to original biologic medicines that allow patients access to biologic therapies for various chronic diseases. Our paper aims to provide an overview of biosimilars in Malaysia with emphasis on the comparison of Malaysian guidelines with guidelines from well-established regulatory agencies, a review of biosimilars' market approval and their reported adverse effects (AEs) as well as clinical trials conducted in Malaysia.

    METHODS: We searched the official websites of the National Pharmaceutical Regulatory Agency (NPRA) Malaysia and three other well-established agencies, online databases of Medline® and EMBASE for guidelines on legislation and regulations of biosimilars. Meanwhile, we extracted the reports of AEs involving biosimilars in Malaysia from the NPRA database and for global AEs from the World Health Organisation VigyLize database. The ClinicalTrials.gov Website by the U.S. National Library of Medicines was the source for data on clinical trials.

    RESULTS: Malaysia followed the principles of the European Medicines Agency biosimilar regulations and issued their guideline in 2008. Since then, NPRA has approved 24 biosimilar products and recorded 499 AE reports, of which 43 (8.6%) were serious. NPRA has also approved ten Phase III clinical trials in Malaysia with four trials still ongoing.

    CONCLUSION: Malaysia follows a stringent regulatory pathway for the approval of biosimilars enacted by well-established regulatory agencies to maintain the quality, efficacy and safety of biosimilars. Introducing biosimilars to the Malaysian market would improve patients' accessibility to biologic therapies.

    Matched MeSH terms: Databases, Factual
  12. Mas Rina Mustaffa, Fatimah Ahmad, Ramlan Mahmod, Shyamala Doraisamy
    MyJurnal
    Multi-feature methods are able to contribute to a more effective method compared to single-feature
    methods since feature fusion methods will be able to close the gap that exists in the single-feature
    methods. This paper presents a feature fusion method, which focuses on extracting colour and shape features for content-based image retrieval (CBIR). The colour feature is extracted based on the proposed Multi-resolution Joint Auto Correlograms (MJAC), while the shape information is obtained through the proposed Extended Generalised Ridgelet-Fourier (EGRF). These features are fused together through a proposed integrated scheme. The feature fusion method has been tested on the SIMPLIcity image database, where several retrieval measurements are utilised to compare the effectiveness of the proposed method with few other comparable methods. The retrieval results show that the proposed Integrated Colour-shape (ICS) descriptor has successfully obtained the best overall retrieval performance in all the retrieval measurements as compared to the benchmark methods, which include precision (53.50%), precision at 11 standard recall levels (52.48%), and rank (17.40).
    Matched MeSH terms: Databases, Factual
  13. Nurul Husna Kamarudin, Nor Azlina Ab Rahman, Zainul Ibrahim Zainuddin
    MyJurnal
    The Medical imaging service in Malaysia is expanding. The presence of
    imaging technologies needs to be supported by homegrown research to optimize their
    use. This study investigated the contribution of researches by Malaysian practitioners to
    the field of Medical imaging in the Malaysian Citation index (MyCite) database. (Copied from article).
    Matched MeSH terms: Databases, Factual
  14. Fakhrul Syafiq, Huzaifah Ismail, Hazleen Aris, Syakiruddin Yusof
    MyJurnal
    Widespread use of mobile devices has resulted in the creation of large amounts of data. An example of such data is the one obtained from the public (crowd) through open calls, known as crowdsourced data. More often than not, the collected data are later used for other purposes such as making predictions. Thus, it is important for crowdsourced data to be recent and accurate, and this means that frequent updating is necessary. One of the challenges in using crowdsourced data is the unpredictable incoming data rate. Therefore, manually updating the data at predetermined intervals is not practical. In this paper, the construction of an algorithm that automatically updates crowdsourced data based on the rate of incoming data is presented. The objective is to ensure that up-to-date and correct crowdsourced data are stored in the database at any point in time so that the information available is updated and accurate; hence, it is reliable. The algorithm was evaluated using a prototype development of a local price-watch information application, CrowdGrocr, in which the algorithm was embedded. The results showed that the algorithm was able to ensure up-to-date information with 94.9% accuracy.
    Matched MeSH terms: Databases, Factual
  15. Loh YC, Tan CS, Yam MF, Oo CW, Omar WMW
    J Pharmacopuncture, 2018 Sep;21(3):203-206.
    PMID: 30283708 DOI: 10.3831/KPI.2018.21.024
    Objectives: There is an increasing number of complex diseases that are progressively more difficult to be controlled using the conventional "single compound, single target" approach as demonstrated in our current modern drug development. TCM might be the new cornerstone of treatment alternative when the current treatment option is no longer as effective or that we have exhausted it as an option. Orthogonal stimulus-response compatibility group study is one of the most frequently employed formulas to produce optimal herbal combination for treatment of multi-syndromic diseases. This approach could solve the relatively low efficacy single drug therapy usage and chronic adverse effects caused by long terms administration of drugs that has been reported in the field of pharmacology and medicine.

    Methods: The present review was based on the Science Direct database search for those related to the TCM and the development of antihypertensive TCM herbal combination using orthogonal stimulus-response compatibility group studies approach.

    Results: Recent studies have demonstrated that the orthogonal stimulus-response compatibility group study approach was most frequently used to formulate TCM herbal combination based on the TCM principles upon the selection of herbs, and the resulting formulated TCM formula exhibited desired outcomes in treating one of global concerned complex multi-syndromic diseases, the hypertension. These promising therapeutic effects were claimed to have been attributed by the holistic signaling mechanism pathways employed by the crude combination of herbs.

    Conclusion: The present review could serve as a guide and prove the feasibility of TCM principles to be used for future pharmacological drug research development.

    Matched MeSH terms: Databases, Factual
  16. Cosmas Julius Abah, Wong, Jane Kong Ling, Anantha Raman Govindasamy
    MyJurnal
    Dictionary production is one of the most effective methods of preserving languages and cultures. The
    Dusunic Family of Languages (DFL) in Sabah, Malaysia would have welcomed the efforts to
    document their languages through dictionary production as there are still lacking of dictionary,
    vocabulary and phrase books. Furthermore, more than half of the languages in DFL are unwritten.
    However, making dictionary conventionally is tedious and time consuming. The Dusunic Family of
    Languages which are facing extinction threats do not have the luxury of time to wait for dictionary
    production via the conventional method. Hence, this study explores the use of a method called Root-
    Oriented Words Generation (ROWG) which is formulated based on spelling orthography of DFL to
    generate one and two-syllable words list. From the words list, root words registers were compiled
    which can then be used as database for dictionary production. Findings of this study showed that
    ROWG was able to generate an exhaustive word lists of DFL and compile a large volume of root
    words register in DFL. Hence, this study was able to highlight the feasibility and viability of using
    ROWG to produce root words register of DFL which could possibly reduce the time for dictionary
    production significantly. In future studies, it is recommended that the ROWG is extended to include
    more than two syllable words. This study showed the potentiality of ROWG to address the looming
    demise of DFL by providing a more efficient way of compiling root words for the purpose of making a
    dictionary.
    Matched MeSH terms: Databases, Factual
  17. Moayedi H, Osouli A, Tien Bui D, Foong LK
    Sensors (Basel), 2019 Oct 29;19(21).
    PMID: 31671801 DOI: 10.3390/s19214698
    Regular optimization techniques have been widely used in landslide-related problems. This paper outlines two novel optimizations of artificial neural network (ANN) using grey wolf optimization (GWO) and biogeography-based optimization (BBO) metaheuristic algorithms in the Ardabil province, Iran. To this end, these algorithms are synthesized with a multi-layer perceptron (MLP) neural network for optimizing its computational parameters. The used spatial database consists of fourteen landslide conditioning factors, namely elevation, slope aspect, land use, plan curvature, profile curvature, soil type, distance to river, distance to road, distance to fault, rainfall, slope degree, stream power index (SPI), topographic wetness index (TWI) and lithology. 70% of the identified landslides are randomly selected to train the proposed models and the remaining 30% is used to evaluate the accuracy of them. Also, the frequency ratio theory is used to analyze the spatial interaction between the landslide and conditioning factors. Obtained values of area under the receiver operating characteristic curve, as well as mean square error and mean absolute error showed that both GWO and BBO hybrid algorithms could efficiently improve the learning capability of the MLP. Besides, the BBO-based ensemble surpasses other implemented models.
    Matched MeSH terms: Databases, Factual
  18. Ali BH, Sulaiman N, Al-Haddad SAR, Atan R, Hassan SLM, Alghrairi M
    Sensors (Basel), 2021 Sep 27;21(19).
    PMID: 34640773 DOI: 10.3390/s21196453
    One of the most dangerous kinds of attacks affecting computers is a distributed denial of services (DDoS) attack. The main goal of this attack is to bring the targeted machine down and make their services unavailable to legal users. This can be accomplished mainly by directing many machines to send a very large number of packets toward the specified machine to consume its resources and stop it from working. We implemented a method using Java based on entropy and sequential probabilities ratio test (ESPRT) methods to identify malicious flows and their switch interfaces that aid them in passing through. Entropy (E) is the first technique, and the sequential probabilities ratio test (SPRT) is the second technique. The entropy method alone compares its results with a certain threshold in order to make a decision. The accuracy and F-scores for entropy results thus changed when the threshold values changed. Using both entropy and SPRT removed the uncertainty associated with the entropy threshold. The false positive rate was also reduced when combining both techniques. Entropy-based detection methods divide incoming traffic into groups of traffic that have the same size. The size of these groups is determined by a parameter called window size. The Defense Advanced Research Projects Agency (DARPA) 1998, DARPA2000, and Canadian Institute for Cybersecurity (CIC-DDoS2019) databases were used to evaluate the implementation of this method. The metric of a confusion matrix was used to compare the ESPRT results with the results of other methods. The accuracy and f-scores for the DARPA 1998 dataset were 0.995 and 0.997, respectively, for the ESPRT method when the window size was set at 50 and 75 packets. The detection rate of ESPRT for the same dataset was 0.995 when the window size was set to 10 packets. The average accuracy for the DARPA 2000 dataset for ESPRT was 0.905, and the detection rate was 0.929. Finally, ESPRT was scalable to a multiple domain topology application.
    Matched MeSH terms: Databases, Factual
  19. Md Idris N, Chiam YK, Varathan KD, Wan Ahmad WA, Chee KH, Liew YM
    Med Biol Eng Comput, 2020 Dec;58(12):3123-3140.
    PMID: 33155096 DOI: 10.1007/s11517-020-02268-9
    Coronary artery disease (CAD) is an important cause of mortality across the globe. Early risk prediction of CAD would be able to reduce the death rate by allowing early and targeted treatments. In healthcare, some studies applied data mining techniques and machine learning algorithms on the risk prediction of CAD using patient data collected by hospitals and medical centers. However, most of these studies used all the attributes in the datasets which might reduce the performance of prediction models due to data redundancy. The objective of this research is to identify significant features to build models for predicting the risk level of patients with CAD. In this research, significant features were selected using three methods (i.e., Chi-squared test, recursive feature elimination, and Embedded Decision Tree). Synthetic Minority Over-sampling Technique (SMOTE) oversampling technique was implemented to address the imbalanced dataset issue. The prediction models were built based on the identified significant features and eight machine learning algorithms, utilizing Acute Coronary Syndrome (ACS) datasets provided by National Cardiovascular Disease Database (NCVD) Malaysia. The prediction models were evaluated and compared using six performance evaluation metrics, and the top-performing models have achieved AUC more than 90%. Graphical abstract.
    Matched MeSH terms: Databases, Factual
  20. Tan GJ, Sulong G, Rahim MSM
    Forensic Sci Int, 2017 Oct;279:41-52.
    PMID: 28843097 DOI: 10.1016/j.forsciint.2017.07.034
    This paper presents a review on the state of the art in offline text-independent writer identification methods for three major languages, namely English, Chinese and Arabic, which were published in literatures from 2011 till 2016. For ease of discussions, we grouped the techniques into three categories: texture-, structure-, and allograph-based. Results are analysed, compared and tabulated along with datasets used for fair and just comparisons. It is observed that during that period, there are significant progresses achieved on English and Arabic; however, the growth on Chinese is rather slow and far from satisfactory in comparison to its wide usage. This is due to its complex writing structure. Meanwhile, issues on datasets used by previous studies are also highlighted because the size matter - accuracy of the writer identification deteriorates as database size increases.
    Matched MeSH terms: Databases, Factual
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