Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 12 of 12 for “"BiLSTM"”.
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Development of an advanced deep learning and neural network method for automatic early detection of mastitis in dairy cattle : A thesis submitted in partial fulfilment of the requirements for the Degree of Doctor of Philosophy at Lincoln University
… trained a Bidirectional Long Short-Term Memory (BiLSTM) network to forecast the cow health state for the following day using supervised learning. The BiLSTM model showed high efficacy in forecasting cow health states, with precision, recall, and F1-scores for each state ranging from 0.92 to 1.00. …
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High performance Deep Learning based Digital Pre-distorters for RF Power Amplifiers
… amplifiers. The simulation results show that BiLSTM based DPDs work the best in terms of improving the linearity performance. We also compare two methodologies of direct learning and indirect learning to develop deep learning-based digital pre-distorters (DL-DPDs) models and evaluate their …
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Neural Networks for Music Emotion Recognition and Social Tags Emotion Representation
… by Bidirectional Long Short-Term Memory (BiLSTM) to capture temporal context sufficiently and predict dynamic music emotion. For the second one, I designed the two-stage learning framework, which uses music segments as model inputs without requiring segment-level labels. By applying the …
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Portfolio Optimization Using a Hybrid Machine Learning Stock Selection Model
… methods are used for prediction: CNN-LSTM and BiLSTM-BO-LightGBM. After training the models, the algorithm creates an optimal portfolio of assets over a simulated year of trading. The symmetric mean absolute percentage error of the algorithms on unseen data evaluates the prediction power. The …
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Machine Learning Applications in Blockchain for Renewable Energy Systems
… with Gated Recurrent Unit (BiLSTM-GRU), is developed for regional solar irradiance forecasting, while a rigorous comparative analysis of ensemble methods such as eXtreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), and Random Forest is conducted …
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Dynamic Hand Gesture Recognition Using Ultrasonic Sonar Sensors and Deep Learning
… used to classify the hand gestures; a Doppler biLSTM network [1] and a CNN [2]. Six basic hand gestures, two in each x- y- and z-axis, and two rotational hand gestures are recorded using both left and right hand at different distances. The gestures were also recorded using both left and right …
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DEVELOPMENT OF TECHNOLOGIES AND METHODS OF ANALYSIS FOR THE FUNCTIONAL EVALUATION OF PERFORMANCE IN FOOTBALL
… machine learning (ML) algorithms, including CNN+BiLSTM neural networks, were trained on accelerometer and gyroscope data for automated technical event detection, achieving 92% macro F1-score for adult populations and 89% for youth. Geofencing algorithms integrate spatial probability models …
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Applied AI for QoE-Aware Video Service and Network Management
… state of the art: deep learning method, i.e., BiLSTM-CNN, to forecast the QoE metrics in future time-steps before they appear on the client’s screen. The proposed approach allows VSM systems to fix a problem before causing a serious issue at the end-user or at least reduce overall QoE …
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Objects Detection and Tracking Using mmWave Technologies
… We used a bi-directional long short-term memory (BiLSTM) network trained with center loss added to the softmax loss to recognize the identities of objects and address the scattered features issue. A Random Forest layer predicted a binary output identifying intruders or insiders. We evaluated our …
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Consistency-aware and LLM-assisted methods for named entity recognition
… A segmentation-based strategy combined with BiLSTM integration is introduced to preserve global context in long clinical notes. Experiments on public and proprietary datasets demonstrate substantial performance improvements, highlighting the effectiveness of structured LLM augmentation for …
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Automatic Extraction of Computer Science Concept Phrases Using a Hybrid Machine Learning Paradigm
With the proliferation of computer science in recent years in modern society, the number of computer science-related employment is expanding quickly. Software engineer has been chosen as the best job for 2023 based on pay, stress level, opportunity for professional growth, and balance between work …
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Beyond words: Understanding emotional shifts in maternal vocalizations through speech emotion recognition models
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01