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    Wyświetlanie 1-11 z 11
    Tytuł:
    Incoherent Discriminative Dictionary Learning for Speech Enhancement
    Autorzy:
    Shaheen, D.
    Dakkak, O. A.
    Wainakh, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/308116.pdf
    Data publikacji:
    2018
    Wydawca:
    Instytut Łączności - Państwowy Instytut Badawczy
    Tematy:
    ADMM
    l1 minimization algorithms
    sparse coding
    speech enhancement
    supervised dictionary learning
    Opis:
    Speech enhancement is one of the many challenging tasks in signal processing, especially in the case of nonstationary speech-like noise. In this paper a new incoherent discriminative dictionary learning algorithm is proposed to model both speech and noise, where the cost function accounts for both “source confusion” and “source distortion” errors, with a regularization term that penalizes the coherence between speech and noise sub-dictionaries. At the enhancement stage, we use sparse coding on the learnt dictionary to find an estimate for both clean speech and noise amplitude spectrum. In the final phase, the Wiener filter is used to refine the clean speech estimate. Experiments on the Noizeus dataset, using two objective speech enhancement measures: frequency-weighted segmental SNR and Perceptual Evaluation of Speech Quality (PESQ) demonstrate that the proposed algorithm outperforms other speech enhancement methods tested.
    Źródło:
    Journal of Telecommunications and Information Technology; 2018, 3; 42-54
    1509-4553
    1899-8852
    Pojawia się w:
    Journal of Telecommunications and Information Technology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Incoherent Dictionary Learning for Sparse Representation in Network Anomaly Detection
    Autorzy:
    Andrysiak, Tomasz
    Saganowski, Łukasz
    Powiązania:
    https://bibliotekanauki.pl/articles/1373708.pdf
    Data publikacji:
    2015
    Wydawca:
    Uniwersytet Jagielloński. Wydawnictwo Uniwersytetu Jagiellońskiego
    Tematy:
    dictionary learning
    sparse representation
    anomaly detection
    Opis:
    In this article we present the use of sparse representation of a signal and incoherent dictionary learning method for the purpose of network traffic analysis. In learning process we use 1D INK-SVD algorithm to detect proper dictionary structure. Anomaly detection is realized by parameter estimation of the analyzed signal and its comparative analysis to network traffic profiles. Efficiency of our method is examined with the use of extended set of test traces from real network traffic. Received experimental results confirm effectiveness of the presented method.
    Źródło:
    Schedae Informaticae; 2015, 24; 63-71
    0860-0295
    2083-8476
    Pojawia się w:
    Schedae Informaticae
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Single Image Super-Resolution through Sparse Representation via Coupled Dictionary learning
    Autorzy:
    Patel, Rutul
    Thakar, Vishvjit
    Joshi, Rutvij
    Powiązania:
    https://bibliotekanauki.pl/articles/226607.pdf
    Data publikacji:
    2020
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    single image super-resolution
    Dictionary Learning
    Sparse representation
    Opis:
    Single Image Super-Resolution (SISR) through sparse representation has received much attention in the past decade due to significant development in sparse coding algorithms. However, recovering high-frequency textures is a major bottleneck of existing SISR algorithms. Considering this, dictionary learning approaches are to be utilized to extract high-frequency textures which improve SISR performance significantly. In this paper, we have proposed the SISR algorithm through sparse representation which involves learning of Low Resolution (LR) and High Resolution (HR) dictionaries simultaneously from the training set. The idea of training coupled dictionaries preserves correlation between HR and LR patches to enhance the Super-resolved image. To demonstrate the effectiveness of the proposed algorithm, a visual comparison is made with popular SISR algorithms and also quantified through quality metrics. The proposed algorithm outperforms compared to existing SISR algorithms qualitatively and quantitatively as shown in experimental results. Furthermore, the performance of our algorithm is remarkable for a smaller training set which involves lesser computational complexity. Therefore, the proposed approach is proven to be superior based upon visual comparisons and quality metrics and have noticeable results at reduced computational complexity.
    Źródło:
    International Journal of Electronics and Telecommunications; 2020, 66, 2; 347-353
    2300-1933
    Pojawia się w:
    International Journal of Electronics and Telecommunications
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Local Characterisation and Detection of Woven Fabric Texture Based on a Sparse Dictionary
    Autorzy:
    Wu, Ying
    Wang, Ren
    Lou, Lin
    Wang, Lali
    Wang, Jun
    Powiązania:
    https://bibliotekanauki.pl/articles/2172000.pdf
    Data publikacji:
    2022
    Wydawca:
    Sieć Badawcza Łukasiewicz - Instytut Biopolimerów i Włókien Chemicznych
    Tematy:
    fabric texture representation
    sparse representation
    weave repeat
    defect detection
    dictionary learning
    Opis:
    To achieve enhanced accuracy of fabric representation and defect detection, an innovative approach using a sparse dictionary with small patches was used for fabric texture characterisation. The effectiveness of the algorithm proposed was tested through comprehensive characterisation by studying eight weave patterns: plain, twill, weft satin, warp satin, basket, honeycomb, compound twill, and diamond twill and detecting fabric defects. Firstly, the main parameters such as dictionary size, patch size, and cardinality T were optimised, and then 40 defect-free fabric samples were characterised by the algorithm proposed. Subsequently, the Impact of the weave pattern was investigated based on the representation result and texture structure. Finally, defective fabrics were detected. The algorithm proposed is an alternative simple and scalable method to characterise fabric texture and detect textile defects in a single step without extracting features or prior information.
    Źródło:
    Fibres & Textiles in Eastern Europe; 2022, 3 (151); 33--40
    1230-3666
    2300-7354
    Pojawia się w:
    Fibres & Textiles in Eastern Europe
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Large-scale hyperspectral image compression via sparse representations based on online learning
    Autorzy:
    Ülkü, İ.
    Kizgut, E.
    Powiązania:
    https://bibliotekanauki.pl/articles/331241.pdf
    Data publikacji:
    2018
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    hyperspectral imaging
    compression algorithm
    dictionary learning
    sparse coding
    obrazowanie wielospektralne
    algorytm kompresji
    nauczanie online
    kodowanie rzadkie
    Opis:
    In this study, proximity based optimization algorithms are used for lossy compression of hyperspectral images that are inherently large scale. This is the first time that such proximity based optimization algorithms are implemented with an online dictionary learning method. Compression performances are compared with the one obtained by various sparse representation algorithms. As a result, proximity based optimization algorithms are listed among the three best ones in terms of compression performance values for all hyperspectral images. Additionally, the applicability of anomaly detection is tested on the reconstructed images.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2018, 28, 1; 197-207
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Fabric Defect Detection and Classifier via Multi-Scale Dictionary Learning and an Adaptive Differential Evolution Optimized Regularization Extreme Learning Machine
    Wykrywanie defektów tkaniny i ich klasyfikacja poprzez zastosowanie maszyny uczącej się (ADE-RELM)
    Autorzy:
    Zhou, Zhiyu
    Wang, Chao
    Gao, Xu
    Zhu, Zefei
    Hu, Xudong
    Zheng, Xiao
    Jiang, Likai
    Powiązania:
    https://bibliotekanauki.pl/articles/233999.pdf
    Data publikacji:
    2019
    Wydawca:
    Sieć Badawcza Łukasiewicz - Instytut Biopolimerów i Włókien Chemicznych
    Tematy:
    defect detection
    multi-scale dictionary learning
    regularisation extreme learning machine
    adaptive differential evolution
    defekty tkaniny
    skuteczność wykrywania defektów
    maszyna ucząca się
    Opis:
    To develop an automatic detection and classifier model for fabric defects, a novel detection and classifier technique based on multi-scale dictionary learning and the adaptive differential evolution algorithm optimised regularisation extreme learning machine (ADE-RELM) is proposed. Firstly in order to speed up dictionary updating under the condition of guaranteeing dictionary sparseness, k-means singular value decomposition (KSVD) dictionary learning is used. Then multi-scale KSVD dictionary learning is presented to extract texture features of textile images more accurately. Finally a unique ADE-RELM is designed to build a defect classifier model. In the training ADE-RELM classifier stage, a self-adaptive mutation operator is used to solve the parameter setting problem of the original differential evolution algorithm, then the adaptive differential evolution algorithm is utilised to calculate the optimal input weights and hidden bias of RELM. The method proposed is committed to detecting common defects like broken warp, broken weft, oil, and the declining warp of grey-level and pure colour fabrics. Experimental results show that compared with the traditional Gabor filter method, morphological operation and local binary pattern, the method proposed in this paper can locate defects precisely and achieve high detection efficiency.
    W celu opracowania automatycznego modelu wykrywania i klasyfikowania defektów tkanin, zaproponowano nowatorską technikę wykrywania i klasyfikowania opartą na zastosowaniu maszyny uczącej się (ADE-RELM). Proponowana metoda ma na celu wykrywanie powszechnych defektów, takich jak przerwana osnowa i wątek oraz zabrudzenia po oleju. Wyniki eksperymentalne pokazują, że w porównaniu z tradycyjną metodą filtrów Gabora, operacją morfologiczną i lokalnym wzorcem binarnym, proponowana w artykule metoda pozwala na precyzyjne zlokalizowanie defektów i osiąga wysoką skuteczność ich wykrywania.
    Źródło:
    Fibres & Textiles in Eastern Europe; 2019, 1 (133); 67-77
    1230-3666
    2300-7354
    Pojawia się w:
    Fibres & Textiles in Eastern Europe
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Electronic Dictionary as a Tool for Integration of Additional Learning Content
    Autorzy:
    Kovacheva, Stefka
    Powiązania:
    https://bibliotekanauki.pl/articles/676994.pdf
    Data publikacji:
    2015
    Wydawca:
    Polska Akademia Nauk. Instytut Slawistyki PAN
    Tematy:
    cultural heritage
    database
    dictionary entry
    electronic dictionary
    e-learning content
    Opis:
    Electronic Dictionary as a Tool for Integration of Additional Learning ContentThis article discusses electronic dictionary as an element of the „Bulgarian cultural and historical heritage under the protection of UNESCO” database developed in IMI (BAS), that will be used to integrate additional learning content. The electronic dictionary is described as an easily accessible book of reference, offering information to the shape, meaning, usage and the origin of words in connection to the cultural-historical heritage sites in Bulgaria, protected by UNESCO. The dictionary targets 9–11 year old students from Bulgarian schools, who study the subjects “Man and Society” in 4th grade and “History and Civilization” in 5th grade.
    Źródło:
    Cognitive Studies; 2015, 15
    2392-2397
    Pojawia się w:
    Cognitive Studies
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Non-formal Elements in Academic Translator Education
    Autorzy:
    Klimkowski, Konrad
    Powiązania:
    https://bibliotekanauki.pl/articles/504736.pdf
    Data publikacji:
    2012
    Wydawca:
    Komisja Nauk Filologicznych Polskiej Akademii Nauk, Oddział we Wrocławiu
    Tematy:
    dictionary
    translation
    translator
    curriculum
    lifelong learning
    Opis:
    The author of the following article propounds that when planning the general translation teaching program for students of translation studies, the methodologists should not narrow it only to the formal curriculum used during regular classes. The author does not refer here to the possibility of broadening the formal program to include practices, internships or meetings with various experts in the field, however, but rather to the redei nition of the notion of curriculum, so that it always includes both formal and informal aspects of the translation studies. The co-existence of the two modules indicates their interdependence in the process of teaching. The primary goal of the informal module is to complement the formal teaching curriculum with various supplementary subject matters, teaching and learning methods as well as interactions that are difficult to implement within the basic frames of the educational program. What is more, the informal initiatives are supposed to give students of translation a chance to take part in various self development programs and events even after they graduate from university, which, as a consequence, provides the students with the opportunity to acquaint themselves with the notion of lifelong learning and, simultaneously, makes them realise how necessary and vital the process is.
    Źródło:
    Academic Journal of Modern Philology; 2012, 1; 33-44
    2299-7164
    2353-3218
    Pojawia się w:
    Academic Journal of Modern Philology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Learning specific academic vocabulary using mall: experience from computer science students
    Autorzy:
    Simanjuntak, Risa Rumentha
    Powiązania:
    https://bibliotekanauki.pl/articles/2096317.pdf
    Data publikacji:
    2020
    Wydawca:
    Uniwersytet Marii Curie-Skłodowskiej w Lublinie. IATEFL Poland Computer Special Interest Group
    Tematy:
    ESAP
    MALL
    mobile dictionary
    Computer Science
    Opis:
    This study investigated the experiences of students in learning specific academic English vocabularies (ESAP) through the use of a mobile dictionary called SPEARA. The mobile app was designed to help the students learn the use of specific words, providing definitions and examples of use from authentic sources. The study aimed at identifying points of learning students experienced when using the mobile-assisted language learning (MALL) by answering two questions: first, to what extent students improved their ESAP using MALL and second, how students perceived MALL for studying specific words in Computer Science. Data for this study were collected from 113 Computer Science students enrolled in English for Academic Purposes classes. Two data sets were compiled in this mixed-method study. The first data set consisted of test scores, and the second data set contained transcripts from interviews with students and students’ essays. Findings showed significant learning improvement in the use of MALL to students’ vocabulary knowledge (SD=0.992). Students perceived leaning using MALL to be both positive and rewarding. Interestingly, students revealed the use of MALL could not replace human interactions. Human interactions could enrich students’ understanding and allowed the exchange of ideas. Further implications on human-interactions in MALL and on the future investigation were also discussed.
    Źródło:
    Teaching English with Technology; 2020, 20, 5; 87-107
    1642-1027
    Pojawia się w:
    Teaching English with Technology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Statistical proper name recognition in Polish economic texts
    Autorzy:
    Marcińczuk, M.
    Piasecki, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/206385.pdf
    Data publikacji:
    2011
    Wydawca:
    Polska Akademia Nauk. Instytut Badań Systemowych PAN
    Tematy:
    proper name recognition
    named entity recognition
    machine learning
    hidden Markov model
    rule-base approach
    dictionary-base approach
    Opis:
    In the paper we present a Proper Name Recognition algorithm based on the Hidden Markov Model (HMM). Recognition of the Proper Names (PN) is treated as the basis for Named Entity Recognition problem in general. The proposed method is based on combining domain-dependent method based on HMM with domain independent methods based on gazetteers and hand-written rules for recognition and post-processing that capture the general properties of Polish PN structure. A large gazetteer with entries described morphologically was acquired from the web. The HMM re-scoring mechanism was applied as a basis for integration of different knowledge sources in PN recognition. Results of experiments on a domain corpus of Polish stock exchange reports, used for training and testing, are presented. A cross-domain evaluation on two other corpora is also presented. Adaptability of the method was analysed by applying the trained model to two other domain corpora.
    Źródło:
    Control and Cybernetics; 2011, 40, 2; 393-418
    0324-8569
    Pojawia się w:
    Control and Cybernetics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Online English Monolingual Learner’s Dictionaries
    Internetowe słowniki jednojęzyczne do nauki angielskiego
    Autorzy:
    Tomaszewska, Magdalena
    Powiązania:
    https://bibliotekanauki.pl/articles/29431226.pdf
    Data publikacji:
    2023
    Wydawca:
    Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
    Tematy:
    słownik jędnojęzyczny
    słownik internetowy
    internetowy słownik jednojęzyczny
    nauka języka angielskiego
    MLD
    online MLD
    online Monolingual Learner’s Dictionary
    learning English
    Opis:
    Due to the development of technology, well-established publishers began to provide their English Monolingual Learner's Dictionaries (MLDs) online and free of charge. Dictionaries of this type have their own history, as well as common and distinctive features. The article presents a brief outline of the subsequent stages of the development of English Monolingual Dictionaries, with special reference to MLDs available online. Also, the article includes a synthetic description of the primary and secondary components of a dictionary entry and demonstrates if these components are present or absent in three online Monolingual Learner's Dictionaries: the Cambridge Dictionary, the Longman Dictionary of Contemporary English, and the Oxford Learner’s Dictionary. The article aims to characterise, compare and contrast some of the features of a typical entry in online English MLDs. Consequently, the scientific approach adopted in the analysis is a mixture of the comparative and the empirical method. Unlike previous topic-related research, the present study shows both common and distinctive features of the mentioned dictionaries and hints at their practical advantages (from the point of view of the end user).
    Źródło:
    Conversatoria Linguistica; 2023, 15; 113-128
    1897-1415
    Pojawia się w:
    Conversatoria Linguistica
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-11 z 11

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