Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

English (EN)·Polski (PL)·Yкраїнський (UK)
Przejdź do strony domowej biblioteki Centralna Biblioteka Wojskowa Link otwiera się w nowym oknie Logo biblioteki Prolib Integro - strona głównaCentralna Biblioteka Wojskowa

Wyszukujesz frazę "support vector machine" wg kryterium: Temat

  Lista filtrów
Wyrównaj
    Wyświetlanie 1-9 z 9
    Tytuł:
    Hybrid deep learning model-based prediction of images related to cyberbullying
    Autorzy:
    Elmezain, Mahmoud
    Malki, Amer
    Gad, Ibrahim
    Atlam, El-Sayed
    Powiązania:
    https://bibliotekanauki.pl/articles/2142490.pdf
    Data publikacji:
    2022
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    cyberbullying
    ResNet50
    MobileNetV2
    support vector machine
    cyberprzemoc
    maszyna wektorów wsparcia
    Opis:
    Cyberbullying has become more widespread as a result of the common use of social media, particularly among teenagers and young people. A lack of studies on the types of advice and support available to victims of bullying has a negative impact on individuals and society. This work proposes a hybrid model based on transformer models in conjunction with a support vector machine (SVM) to classify our own data set images. First, seven different convolutional neural network architectures are employed to decide which is best in terms of results. Second, feature extraction is performed using four top models, namely, ResNet50, EfficientNetB0, MobileNet and Xception architectures. In addition, each architecture extracts the same number of features as the number of images in the data set, and these features are concatenated. Finally, the features are optimized and then provided as input to the SVM classifier. The accuracy rate of the proposed merged models with the SVM classifier achieved 96.05%. Furthermore, the classification precision of the proposed merged model is 99% in the bullying class and 93% in the non-bullying class. According to these results, bullying has a negative impact on students’ academic performance. The results help stakeholders to take necessary measures against bullies and increase the community’s awareness of this phenomenon.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2022, 32, 2; 323--334
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Multiple-instance learning with pairwise instance similarity
    Autorzy:
    Yuan, L.
    Liu, J.
    Tang, X.
    Powiązania:
    https://bibliotekanauki.pl/articles/330821.pdf
    Data publikacji:
    2014
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    multiple instance learning
    instance selection
    similarity
    support vector machine (SVM)
    uczenie maszynowe
    podobieństwo
    metoda wektorów wspomagających
    Opis:
    Multiple-Instance Learning (MIL) has attracted much attention of the machine learning community in recent years and many real-world applications have been successfully formulated as MIL problems. Over the past few years, several Instance Selection-based MIL (ISMIL) algorithms have been presented by using the concept of the embedding space. Although they delivered very promising performance, they often require long computation times for instance selection, leading to a low efficiency of the whole learning process. In this paper, we propose a simple and efficient ISMIL algorithm based on the similarity of pairwise instances within a bag. The basic idea is selecting from every training bag a pair of the most similar instances as instance prototypes and then mapping training bags into the embedding space that is constructed from all the instance prototypes. Thus, the MIL problem can be solved with the standard supervised learning techniques, such as support vector machines. Experiments show that the proposed algorithm is more efficient than its competitors and highly comparable with them in terms of classification accuracy. Moreover, the testing of noise sensitivity demonstrates that our MIL algorithm is very robust to labeling noise.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2014, 24, 3; 567-577
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Using the one-versus-rest strategy with samples balancing to improve pairwise coupling classification
    Autorzy:
    Chmielnicki, W.
    Stąpor, K.
    Powiązania:
    https://bibliotekanauki.pl/articles/330749.pdf
    Data publikacji:
    2016
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    multiclass classification
    pairwise coupling
    problem decomposition
    support vector machine (SVM)
    klasyfikacja wieloklasowa
    rozkład problemu
    maszyna wektorów wspierających
    Opis:
    The simplest classification task is to divide a set of objects into two classes, but most of the problems we find in real life applications are multi-class. There are many methods of decomposing such a task into a set of smaller classification problems involving two classes only. Among the methods, pairwise coupling proposed by Hastie and Tibshirani (1998) is one of the best known. Its principle is to separate each pair of classes ignoring the remaining ones. Then all objects are tested against these classifiers and a voting scheme is applied using pairwise class probability estimates in a joint probability estimate for all classes. A closer look at the pairwise strategy shows the problem which impacts the final result. Each binary classifier votes for each object even if it does not belong to one of the two classes which it is trained on. This problem is addressed in our strategy. We propose to use additional classifiers to select the objects which will be considered by the pairwise classifiers. A similar solution was proposed by Moreira and Mayoraz (1998), but they use classifiers which are biased according to imbalance in the number of samples representing classes.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2016, 26, 1; 191-201
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A primal sub-gradient method for structured classification with the averaged sum loss
    Autorzy:
    Mančev, D.
    Todorović, B.
    Powiązania:
    https://bibliotekanauki.pl/articles/331050.pdf
    Data publikacji:
    2014
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    structured classification
    support vector machine (SVM)
    subgradient method
    sequence labeling
    klasyfikacja strukturalna
    maszyna wektorów nośnych
    rozpoznawanie wzorca
    Opis:
    We present a primal sub-gradient method for structured SVM optimization defined with the averaged sum of hinge losses inside each example. Compared with the mini-batch version of the Pegasos algorithm for the structured case, which deals with a single structure from each of multiple examples, our algorithm considers multiple structures from a single example in one update. This approach should increase the amount of information learned from the example. We show that the proposed version with the averaged sum loss has at least the same guarantees in terms of the prediction loss as the stochastic version. Experiments are conducted on two sequence labeling problems, shallow parsing and part-of-speech tagging, and also include a comparison with other popular sequential structured learning algorithms.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2014, 24, 4; 917-930
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Efficient decision trees for multi-class support vector machines using entropy and generalization error estimation
    Autorzy:
    Kantavat, P.
    Kijsirikul, B.
    Songsiri, P.
    Fukui, K. I.
    Numao, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/330532.pdf
    Data publikacji:
    2018
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    support vector machine
    multi-class classification
    generalization error
    decision tree
    maszyna wektorów wsparcia
    klasyfikacja wieloklasowa
    błąd generalizacji
    drzewo decyzyjne
    Opis:
    We propose new methods for support vector machines using a tree architecture for multi-class classification. In each node of the tree, we select an appropriate binary classifier, using entropy and generalization error estimation, then group the examples into positive and negative classes based on the selected classifier, and train a new classifier for use in the classification phase. The proposed methods can work in time complexity between O(log2 N) and O(N), where N is the number of classes. We compare the performance of our methods with traditional techniques on the UCI machine learning repository using 10-fold cross-validation. The experimental results show that the methods are very useful for problems that need fast classification time or those with a large number of classes, since the proposed methods run much faster than the traditional techniques but still provide comparable accuracy.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2018, 28, 4; 705-717
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A support vector machine with the tabu search algorithm for freeway incident detection
    Autorzy:
    Yao, B.
    Hu, P.
    Zhang, M.
    Jin, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/329943.pdf
    Data publikacji:
    2014
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    automated incident detection
    support vector machine (SVM)
    tabu search
    freeway
    maszyna wektorów wspierających
    odcinek swobodny trasy
    algorytm tabu search
    Opis:
    Automated Incident Detection (AID) is an important part of Advanced Traffic Management and Information Systems (ATMISs). An automated incident detection system can effectively provide information on an incident, which can help initiate the required measure to reduce the influence of the incident. To accurately detect incidents in expressways, a Support Vector Machine (SVM) is used in this paper. Since the selection of optimal parameters for the SVM can improve prediction accuracy, the tabu search algorithm is employed to optimize the SVM parameters. The proposed model is evaluated with data for two freeways in China. The results show that the tabu search algorithm can effectively provide better parameter values for the SVM, and SVM models outperform Artificial Neural Networks (ANNs) in freeway incident detection.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2014, 24, 2; 397-404
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Facial expression recognition under difficult conditions: A comprehensive study on edge directional texture patterns
    Autorzy:
    Ahmed, F.
    Kabir, M. H.
    Powiązania:
    https://bibliotekanauki.pl/articles/331105.pdf
    Data publikacji:
    2018
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    directional ternary pattern
    compressed DTP
    facial feature descriptor
    texture encoding
    support vector machine
    deskryptor cech
    kodowanie struktury
    maszyna wektorów wsparcia
    Opis:
    In recent years, research in automated facial expression recognition has attained significant attention for its potential applicability in human–computer interaction, surveillance systems, animation, and consumer electronics. However, recognition in uncontrolled environments under the presence of illumination and pose variations, low-resolution video, occlusion, and random noise is still a challenging research problem. In this paper, we investigate recognition of facial expression in difficult conditions by means of an effective facial feature descriptor, namely the directional ternary pattern (DTP). Given a face image, the DTP operator describes the facial feature by quantizing the eight-directional edge response values, capturing essential texture properties, such as presence of edges, corners, points, lines, etc. We also present an enhancement of the basic DTP encoding method, namely the compressed DTP (cDTP) that can describe the local texture more effectively with fewer features. The recognition performances of the proposed DTP and cDTP descriptors are evaluated using the Cohn–Kanade (CK) and the Japanese female facial expression (JAFFE) database. In our experiments, we simulate difficult conditions using original database images with lighting variations, low-resolution images obtained by down-sampling the original, and images corrupted with Gaussian noise. In all cases, the proposed method outperforms some of the well-known face feature descriptors.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2018, 28, 2; 399-409
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Adaptive control scheme based on the least squares support vector machine network
    Autorzy:
    Mahmoud, T. K.
    Powiązania:
    https://bibliotekanauki.pl/articles/930155.pdf
    Data publikacji:
    2011
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    modelowanie systemu
    system nieliniowy
    system sterowania
    sieć neuronowa
    maszyna wektorów wspierających
    support vector machine (SVM)
    neural network
    nonlinear system modeling
    nonlinear system control
    pH control
    Opis:
    Recently, a new type of neural networks called Least Squares Support Vector Machines (LS-SVMs) has been receiving increasing attention in nonlinear system identification and control due to its generalization performance. This paper develops a stable adaptive control scheme using the LS-SVM network. The developed control scheme includes two parts: the identification part that uses a modified structure of LS-SVM neural networks called the multi-resolution wavelet least squares support vector machine network (MRWLS-SVM) as a predictor model, and the controller part that is developed to track a reference trajectory. By means of the Lyapunov stability criterion, stability analysis for the tracking errors is performed. Finally, simulation studies are performed to demonstrate the capability of the developed approach in controlling a pH process.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2011, 21, 4; 685-696
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Automatic parametric fault detection in complex analog systems based on a method of minimum node selection
    Autorzy:
    Bilski, A.
    Wojciechowski, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/330761.pdf
    Data publikacji:
    2016
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    complex analog system
    support vector machine (SVM)
    tabu search
    genetic algorithm
    parametric fault detection
    system analogowy
    maszyna wektorów wspierających
    metoda tabu search
    algorytm genetyczny
    detekcja uszkodzeń
    Opis:
    The aim of this paper is to introduce a strategy to find a minimal set of test nodes for diagnostics of complex analog systems with single parametric faults using the support vector machine (SVM) classifier as a fault locator. The results of diagnostics of a video amplifier and a low-pass filter using tabu search along with genetic algorithms (GAs) as node selectors in conjunction with the SVM fault classifier are presented. General principles of the diagnostic procedure are first introduced, and then the proposed approach is discussed in detail. Diagnostic results confirm the usefulness of the method and its computational requirements. Conclusions on its wider applicability are provided as well.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2016, 26, 3; 655-668
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-9 z 9

      Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies