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 9 of 9 for “"robust deep learning"”.
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Efficient and Robust Deep Learning for Robotics
L'abstract è presente nell'allegato / the abstract is in the attachment
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Robust Deep Learning Methodologies for Weakly Supervised Remote Sensing Image Classification
… change studies and environmental monitoring. Deep learning (DL) has proven very effective in addressing the analytical challenges posed by this data, excelling in image analysis and sequential data processing. However, in remote sensing (RS), DL is often hindered by scarce and imperfect …
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The Dark Side of the Eye: Towards Robust Deep Learning Models for Uveal Melanoma Screening
… often results in invasive treatments, which deeply affect both the patient's quality of life and the healthcare system. For this reason, improving the efficiency and reliability of screening procedures is crucial. Typically, a diagnosis of UM is made through manual ophthalmic image analysis. …
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On practical robustness of machine learning systems
We consider the importance of robustness in evaluating machine learning systems, an in particular systems involving deep learning. We consider these systems' vulnerability to adversarial examples--subtle, crafted perturbations to inputs which induce large change in output. We show that these …
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Assessing Structure–Property Relationships of Crystal Materials using Deep Learning
In recent years, deep learning technologies have received huge attention and interest in the field of high-performance material design. This is primarily because deep learning algorithms in nature have huge advantages over the conventional machine learning models in processing massive amounts of …
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An Investigation into the Performance of Ethnicity Verification Between Humans and Machine Learning Algorithms
… dataset. To make the system more accurate and robust, Deep Learning models are employed for ethnicity classification. Various state-of-the-art Deep models are trained on a range of facial image conditions, i.e. full face and partial-face images, plus standalone feature components such as the …
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An Investigation into the Performance of Ethnicity Verification Between Humans and Machine Learning Algorithms
… dataset. To make the system more accurate and robust, Deep Learning models are employed for ethnicity classification. Various state-of-the-art Deep models are trained on a range of facial image conditions, i.e. full face and partial-face images, plus standalone feature components such as the …
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Efficient, robust and uncertainty aware mobile health
… illness. This data can be fed into machine learning algorithms aiming to help practitioners better assess the progress of the patient or other aspects of the disease evolution. Therefore, it is essential to have accurate model predictions and, equally significantly, a better understanding of …
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Example weighting for deep representation learning
… Therefore, example weighting is universal in deep learning. Partially arising from the recent work on the risky memorisation behaviours of deep neural networks (Arpit et al., 2017; Zhang et al., 2017b), example weighting becomes an active research filed (Chang et al., 2017; Toneva et al., …