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Found 4 essays matching the above criteria.
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1. Evaluating Transfer Learning Models on Synthetic Data for Beverage Label Image Retrieval : A Comparative Study
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Information retrieval is a research area that has seen improvements with the development of deep learning and artificial neural networks. The vast amount of image data available today has made it possible to train computer vision models for efficient image search. READ MORE
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2. Geospatial Trip Data Generation Using Deep Neural Networks
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Development of deep learning methods is dependent majorly on availability of large amounts of high quality data. To tackle the problem of data scarcity one of the workarounds is to generate synthetic data using deep learning methods. READ MORE
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3. Evaluating Unsupervised Methods for Out-of-Distribution Detection on Semantically Similar Image Data
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Out-of-distribution detection considers methods used to detect data that deviates from the underlying data distribution used to train some machine learning model. This is an important topic, as artificial neural networks have previously been shown to be capable of producing arbitrarily confident predictions, even for anomalous samples that deviate from the training distribution. READ MORE
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4. Synthetic Meta-Learning: : Learning to learn real-world tasks with synthetic data
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Meta-learning is an approach to machine learning that teaches models how to learn new tasks with only a handful of examples. However, meta-learning requires a large labeled dataset during its initial meta-learning phase, which restricts what domains meta-learning can be used in. READ MORE
