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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 5 6 7 8 9...50 Hits 81 – 100 of 990 81 Discriminative feature modeling for statistical speech recognition ... Tüske, Zoltán. - : RWTH Aachen University, 2021 BASE Show details 82 Towards Learning Terminological Concept Systems from Multilingual Natural Language Text ... Wachowiak, Lennart; Lang, Christian; Heinisch, Barbara. - : Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2021 BASE Show details 83 How the input shapes the acquisition of verb morphology: elicited production and computational modelling in two highly inflected languages ... Engelmann, Felix. - : Open Science Framework, 2021 BASE Show details 84 Which Theory of Language for Deep Neural Networks? Speech and Cognition in Humans and Machines ... Capone, Luca. - : Technology and Language, 2(4), 29-60, 2021 BASE Show details 85 Data-Driven Analysis of Zebra Finch Song Copying and Learning Brudner, Samuel Navickas. - 2021 BASE Show details 86 Sentiment Analysis of Amazon Electronic Product Reviews using Deep Learning Abah, Jemimah Ojima. - : Dublin Business School, 2021 BASE Show details 87 Phonetic processing in speech sound disorder (Gerwin et al., 2021) ... Gerwin, Katelyn L.; Brosseau-Lapré, Françoise; Weber, Christine. - : ASHA journals, 2021 BASE Show details 88 Machine Learning Methods for Automatic Silent Speech Recognition Using a Wearable Graphene Strain Gauge Sensor. ... Ravenscroft, Dafydd; Prattis, Ioannis; Kandukuri, Tharun. - : Apollo - University of Cambridge Repository, 2021 BASE Show details 89 Phonetic processing in speech sound disorder (Gerwin et al., 2021) ... Gerwin, Katelyn L.; Brosseau-Lapré, Françoise; Weber, Christine. - : ASHA journals, 2021 BASE Show details 90 Automated Paraphrase Quality Assessment Using Language Models and Transfer Learning Bogdan Nicula; Mihai Dascalu; Natalie N. Newton; Ellen Orcutt; Danielle S. McNamara In: Computers; Volume 10; Issue 12; Pages: 166 (2021) BASE Show details 91 Extracting Semantic Relationships in Greek Literary Texts Despina Christou; Grigorios Tsoumakas In: Sustainability ; Volume 13 ; Issue 16 (2021) BASE Show details 92 Machine Learning Methods for Automatic Silent Speech Recognition Using a Wearable Graphene Strain Gauge Sensor Dafydd Ravenscroft; Ioannis Prattis; Tharun Kandukuri; Yarjan Abdul Samad; Giorgio Mallia; Luigi G. Occhipinti In: Sensors; Volume 22; Issue 1; Pages: 299 (2021) BASE Show details 93 Burnout, Resilience, and COVID-19 among Teachers: Predictive Capacity of an Artificial Neural Network Juan Pedro Martínez-Ramón; Francisco Manuel Morales-Rodríguez; Sergio Pérez-López In: Applied Sciences ; Volume 11 ; Issue 17 (2021) BASE Show details 94 Application of Artificial Intelligence in Stock Market Forecasting: A Critique, Review, and Research Agenda Ritika Chopra; Gagan Deep Sharma In: Journal of Risk and Financial Management ; Volume 14 ; Issue 11 (2021) BASE Show details 95 Authorship Attribution of Social Media and Literary Russian-Language Texts Using Machine Learning Methods and Feature Selection Anastasia Fedotova; Aleksandr Romanov; Anna Kurtukova; Alexander Shelupanov In: Future Internet; Volume 14; Issue 1; Pages: 4 (2021) Abstract: Authorship attribution is one of the important fields of natural language processing (NLP). Its popularity is due to the relevance of implementing solutions for information security, as well as copyright protection, various linguistic studies, in particular, researches of social networks. The article is a continuation of the series of studies aimed at the identification of the Russian-language text’s author and reducing the required text volume. The focus of the study was aimed at the attribution of textual data created as a product of human online activity. The effectiveness of the models was evaluated on the two Russian-language datasets: literary texts and short comments from users of social networks. Classical machine learning (ML) algorithms, popular neural networks (NN) architectures, and their hybrids, including convolutional neural network (CNN), networks with long short-term memory (LSTM), Bidirectional Encoder Representations from Transformers (BERT), and fastText, that have not been used in previous studies, were applied to solve the problem. A particular experiment was devoted to the selection of informative features using genetic algorithms (GA) and evaluation of the classifier trained on the optimal feature space. Using fastText or a combination of support vector machine (SVM) with GA reduced the time costs by half in comparison with deep NNs with comparable accuracy. The average accuracy for literary texts was 80.4% using SVM combined with GA, 82.3% using deep NNs, and 82.1% using fastText. For social media comments, results were 66.3%, 73.2%, and 68.1%, respectively. Keyword: authorship identification; deep neural networks; fastText; genetic algorithms; machine learning; natural language processing; support vector machine URL: https://doi.org/10.3390/fi14010004 BASE Hide details 96 Classification of Problem and Solution Strings in Scientific Texts: Evaluation of the Effectiveness of Machine Learning Classifiers and Deep Neural Networks Rohit Bhuvaneshwar Mishra; Hongbing Jiang In: Applied Sciences ; Volume 11 ; Issue 21 (2021) BASE Show details 97 Optimization of Convolutional Neural Networks Architectures Using PSO for Sign Language Recognition Jonathan Fregoso; Claudia I. Gonzalez; Gabriela E. Martinez In: Axioms; Volume 10; Issue 3; Pages: 139 (2021) BASE Show details 98 Presentation Attack Detection on Limited-Resource Devices Using Deep Neural Classifiers Trained on Consistent Spectrogram Fragments Kacper Kubicki; Paweł Kapusta; Krzysztof Ślot In: Sensors ; Volume 21 ; Issue 22 (2021) BASE Show details 99 Sentence Compression Using BERT and Graph Convolutional Networks Yo-Han Park; Gyong-Ho Lee; Yong-Seok Choi... In: Applied Sciences ; Volume 11 ; Issue 21 (2021) BASE Show details 100 Introducing Various Semantic Models for Amharic: Experimentation and Evaluation with Multiple Tasks and Datasets Seid Muhie Yimam; Abinew Ali Ayele; Gopalakrishnan Venkatesh... In: Future Internet ; Volume 13 ; Issue 11 (2021) BASE Show details Page: 1 2 3 4 5 6 7 8 9...50

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