Essays about: "data augmentation"
Showing result 16 - 20 of 179 essays containing the words data augmentation.
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16. Volumetric Image Segmentation of Lizard Brains
University essay from KTH/Tillämpad fysikAbstract : Accurate measurement brain region volumes are important in studying brain plasticity, which brings insight into the fundamental mechanisms in animal, memory, cognitive, and behavior research. The traditional methods of brain volume measurements are ellipsoid or histology. READ MORE
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17. Comparative Analysis of Transformer and CNN Based Models for 2D Brain Tumor Segmentation
University essay from Linköpings universitet/Institutionen för medicinsk teknikAbstract : A brain tumor is an abnormal growth of cells within the brain, which can be categorized into primary and secondary tumor types. The most common type of primary tumors in adults are gliomas, which can be further classified into high-grade gliomas (HGGs) and low-grade gliomas (LGGs). READ MORE
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18. Ankle Torque Estimation Using HDEMG Driven CNN-LSTM Model and Data Augmentation
University essay from KTH/Medicinteknik och hälsosystemAbstract : Robotic-powered exoskeletons are increasingly used to assist patients with movement disorders in daily life and rehabilitation. Accurately estimating joint torque, especially for dynamic movement conditions using EMG, is crucial for effective assistance. READ MORE
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19. Deep convolution neural network for attention decoding in multi-channel EEG with conditional variational autoencoder for data augmentation
University essay from Lunds universitet/Institutionen för reglerteknikAbstract : Objectives: This project aims to develop a deep learning-based attention decoding system that can distinguish between noise and speech in noise and also identify the direction of attended speech from the brain data recorded with electroencephalography (EEG) instruments. Two deep convolutional neural network (DCNN) models will be designed: (1) one DCNN model capable of classifying incoming segments of sound as speech or speech in background noise, and (2) one DCNN model identifying the direction (left vs. READ MORE
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20. Exploring Normalizing Flow Modifications for Improved Model Expressivity
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Normalizing flows represent a class of generative models that exhibit a number of attractive properties, but do not always achieve state-of-the-art performance when it comes to perceived naturalness of generated samples. To improve the quality of generated samples, this thesis examines methods to enhance the expressivity of discrete-time normalizing flow models and thus their ability to capture different aspects of the data. READ MORE