Essays about: "overfitting"
Showing result 21 - 25 of 83 essays containing the word overfitting.
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21. Analyzing the Negative Log-Likelihood Loss in Generative Modeling
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Maximum-Likelihood Estimation (MLE) is a classic model-fitting method from probability theory. However, it has been argued repeatedly that MLE is inappropriate for synthesis applications, since its priorities are at odds with important principles of human perception, and that, e.g. READ MORE
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22. Data Driven Energy Efficiency of Ships
University essay from Högskolan i Halmstad/Akademin för informationsteknologiAbstract : Decreasing the fuel consumption and thus greenhouse gas emissions of vessels has emerged as a critical topic for both ship operators and policy makers in recent years. The speed of vessels has long been recognized to have highest impact on fuel consumption. READ MORE
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23. Combined Regularisation Techniques for Artificial Neural Networks
University essay from Lunds universitet/Beräkningsbiologi och biologisk fysik - Genomgår omorganisationAbstract : Artificial neural networks are prone to overfitting – the process of learning details specific to a particular training data set. Success in preventing overfitting through combining the L2 and dropout regularisation techniques has led to the combination’s recent popularity. READ MORE
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24. The research of background removal applied to fashion data : The necessity analysis of background removal for fashion data
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Fashion understanding is a hot topic in computer vision, with many applications having a great business value in the market. It remains a difficult challenge for computer vision due to the immense diversity of garments and a wide range of scenes and backgrounds. READ MORE
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25. Synthesis of Pediatric Brain Tumor Image With Mass Effect
University essay from KTH/Skolan för kemi, bioteknologi och hälsa (CBH)Abstract : During the last few years, deep learning-based techniques have made much progress in the medical image processing field, such as segmentation and registration. The main characteristic of these methods is the large demand of medical images to do model training. READ MORE