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 11 of 11 for “"attention model"”.
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A computational model of visual attention.
Visual attention is a process by which the Human Visual System (HVS) selects most important information from a scene. Visual attention models are computational or mathematical models developed to predict this information. The performance of the state-of-the-art visual attention models is limited in …
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End-To-End Text Detection Using Deep Learning
… used for text detection are box detection models and fully convolutional models. Box detection models suffer from the nature of the annotations, which may be too coarse to provide detailed supervision. Fully convolutional models learn to generate pixel-wise maps that represent the location …
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Video Content Extraction: Scene Segmentation, Linking And Attention Detection
… content, we have developed a spatiotemporal attention detection model for videos. Our general framework for temporal scene segmentation, which is applicable to several video domains, is formulated in a statistical fashion and uses the Markov chain Monte Carlo (MCMC) technique to determine the …
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An Attention LSTM U-Net Model for Drosophila Melanogaster Heart Tube Segmentation
… is often used as a cardiac disease model, where optical coherence microscopy (OCM) is used to image and analyze its beating dynamics. As OCM often generates a large volume of images, automated image segmentation is necessary to quantify the heart beating efficiently. Our most recent …
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Forecasting Energy Consumption using Sequence to Sequence Attention models
… (S2S) Recurrent Neural Networks (RNNs) with attention for electrical load forecasting. The S2S and S2S attention architectures commonly used for neural machine translation are adapted for energy forecasting. An RNN enables capturing time dependencies present in the load data, while the S2S …
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Spontaneous speech recognition using visual context-aware language models
… knowledge to generate class-based language models conditioned on the objects present in the scene as well as a spatial language model that predicts the occurrences of spatial terms conditioned on target and landmark objects. The speech recognizer in Fuse uses a weighted mixture of these …
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Audio-visual football video analysis, from structure detection to attention analysis
… attack temporal structure decomposition, and attention-based highlight identification. Replay segments convey the most important contents in sports videos. It is an efficient approach to collect game highlights by detecting replay segments. However, replay is an artefact of editing, which …
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Developing Deep Learning Models for Depression Detection in Texts
… depression. Consequently, using deep learning models to detect depressed and non-depressed individuals based on social media posts, by analyzing the words being posted, has become the focus of recent research. The lack of big-sized depression-labeled datasets for training models for depression …
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Exploration of Techniques for Working with Sparse Data when Applying Natural Language Processing to Assist a Qualitative Data Analysis of a COVID-19 Open Innovation Community
… strategies, to enhance the efficacy of various models, including Logistic Regression, Naive Bayes, Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and particularly the Self-Attention model. The proposed framework, identified for its superior performance, demonstrates a …
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Applying Language Models To Patient Health Records: Acronym Expansion, Long Document Classification and Explainable Predictions
… medical acronyms in context, (2) building models that can analyze multi-modal data (structured and unstructured patient EHR data) that includes lengthy clinical notes to study a stigmatized condition, namely opioid prescribing patterns and opioid use disorder (OUD) risk, and (3) developing …
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Neuronal encoding of natural imagery in dragonfly motion pathways
… of the brain. Insects represent an excellent model for investigating how vision operates as they often lead rich visual lives while possessing relatively simple brains. Among insects, aerial predators such as the dragonfly face additional survival tasks. Not only must aerial predators …