Essays about: "slow learning"
Showing result 1 - 5 of 103 essays containing the words slow learning.
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1. Decoding the surface code using graph neural networks
University essay from Göteborgs universitet / Institutionen för fysikAbstract : Quantum error correction is essential to achieve fault-tolerant quantum computation in the presence of noisy qubits. Among the most promising approaches to quantum error correction is the surface code, thanks to a scalable two-dimensional architecture, only nearest-neighbor interactions, and a high error threshold. Decoding the surface code, i.e. READ MORE
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2. IDENTIFICATION OF ENVIRONMENTALLY RELEVANT BENTHIC FORAMINIFERA FROM THE SKAGERRAK FJORDS BY DEEP LEARNING IMAGE MODELING
University essay from Göteborgs universitet / Institutionen för biologi och miljövetenskapAbstract : Over the several past decades, there has been increasing interest in using foraminifera as environmental indicators for coastal marine environments. As compared to macrofauna, which are currently used in environmental studies, foraminifera offer several distinct advantages as bioindicators, including short generation times, a high number of individuals per small sample volume, hard and durable tests with high preservation potential, and low cost of sample extraction. READ MORE
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3. Quality enhancement of time-resolved computed tomography scans with cycleGAN
University essay from Lunds universitet/Synkrotronljusfysik; Lunds universitet/Fysiska institutionenAbstract : Time-resolved x-ray tomography enables us to dynamically and non-destructively study the interior of a specimen. The obtainable temporal resolution is limited by the x-ray flux and the desired spatial resolution. READ MORE
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4. Customer churn prediction in a slow fashion e-commerce context : An analysis of the effect of static data in customer churn prediction
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Survival analysis is a subfield of statistics where the goal is to analyse and model the data where the outcome is the time until the occurrence of an event of interest. Because of the intrinsic temporal nature of the analysis, the employment of more recently developed sequential models (Recurrent Neural Network (RNN) and Long Short Term Memory (LSTM)) has been paired with the use of dynamic temporal features, in contrast with the past reliance on static ones. READ MORE
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5. Fine-Tuning Parameters in CT
University essay from KTH/Skolan för teknikvetenskap (SCI)Abstract : Computed tomography (CT) is a medical imaging technique that usesX-rays to obtain a reconstruction of an object. The term acquisition ge-ometry refers to the arrangement of imaging sensors and the X-ray sourceas well as the procedure used for data collection. READ MORE