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Novice programmers’ emotion and competency assessments using machine learning on physiological data / Fatima Jannat
Published 2022“…The Long Short-term Memory (LSTM) deep learning model was chosen for classifying programming learners according to their performance. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through use of a robust and efficient optimization algorithm in learning process of GEP approach. To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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Machine learning predictions of stock market pattern using Econophysics approach
Published 2025“…By leveraging machine learning algorithms, such as Long Short-Term Memory (LSTM), the predictions generated closely follow the actual stock price movements for Inari Amertron Berhad. …”
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Measuring GPU-accelerated parallel SVM performance using large datasets for multi-class machine learning problem
Published 2023Conference Paper -
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Enhancing obfuscation technique for protecting source code against software reverse engineering
Published 2019“…The proposed technique can be enhanced in the future to protect games applications and mobile applications that are developed by java; it can improve the software development industry. …”
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Algorithms for moderating effect of emotional value from a cross-media data fusion perspective: a case study of Chinese dating reality shows
Published 2026“…During the feature extraction part, different machine-learning models are applied: Bidirectional Encoder Representations from Transformers (BERT) or Enhanced Representation through Knowledge Integration (ERNIE) for text; Convolutional Recurrent Neural Network (CRNN), and Bidirectional Long Short-Term Memory (Bi-LSTM) for audio; and Residual Neural Network (ResNet50) and Inflated 3D Convolutional Network (I3D) for video. …”
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Design & Development of a Robotic System Using LEGO Mindstorm
Published 2006“…Since the model is built using LEGO bricks, the model is fully customized, in term of its applications, to perform any relevant tasks. …”
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NON-VERBAL HUMAN-ROBOT INTERACTION USING NEURAL NETWORK FOR THE APPLICATION OF SERVICE ROBOT
Published 2023“…The face tracking model was trained using a Long Short-Term Memory (LSTM) neural network, which is based on deep learning. …”
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NON-VERBAL HUMAN-ROBOT INTERACTION USING NEURAL NETWORK FOR THE APPLICATION OF SERVICE ROBOT
Published 2023“…The face tracking model was trained using a Long Short-Term Memory (LSTM) neural network, which is based on deep learning. …”
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NON-VERBAL HUMAN-ROBOT INTERACTION USING NEURAL NETWORK FOR THE APPLICATION OF SERVICE ROBOT
Published 2023“…The face tracking model was trained using a Long Short-Term Memory (LSTM) neural network, which is based on deep learning. …”
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Non-Verbal Human-Robot Interaction Using Neural Network for The Application of Service Robot
Published 2023“…The face tracking model was trained using a Long Short-Term Memory (LSTM) neural network, which is based on deep learning. …”
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NON-VERBAL HUMAN-ROBOT INTERACTION USING NEURAL NETWORK FOR THE APPLICATION OF SERVICE ROBOT
Published 2023“…The face tracking model was trained using a Long Short-Term Memory (LSTM) neural network, which is based on deep learning. …”
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NON-VERBAL HUMAN-ROBOT INTERACTION USING NEURAL NETWORK FOR THE APPLICATION OF SERVICE ROBOT
Published 2023“…The face tracking model was trained using a Long Short-Term Memory (LSTM) neural network, which is based on deep learning. …”
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NON-VERBAL HUMAN-ROBOT INTERACTION USING NEURAL NETWORK FOR THE APPLICATION OF SERVICE ROBOT
Published 2023“…The face tracking model was trained using a Long Short-Term Memory (LSTM) neural network, which is based on deep learning. …”
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Translating medical image to radiological report: Adaptive multilevel multi-attention approach
Published 2022“…The Word2Vec and FastText word embeddings are trained on medical reports to acquire radiological knowledge and further used as textual encoders, feeding as input to Bi-directional Long Short Term Memory (Bi-LSTM) network to learn the co-relationship between medical terminologies in radiological reports. …”
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NON-VERBAL HUMAN-ROBOT INTERACTION USING NEURAL NETWORK FOR THE APPLICATION OF SERVICE ROBOT
Published 2023“…The face tracking model was trained using a Long Short-Term Memory (LSTM) neural network, which is based on deep learning. …”
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NON-VERBAL HUMAN-ROBOT INTERACTION USING NEURAL NETWORK FOR THE APPLICATION OF SERVICE ROBOT
Published 2023“…The face tracking model was trained using a Long Short-Term Memory (LSTM) neural network, which is based on deep learning. …”
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