Essays about: "Neurala"
Showing result 16 - 20 of 774 essays containing the word Neurala.
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16. Predicting user churn using temporal information : Early detection of churning users with machine learning using log-level data from a MedTech application
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : User retention is a critical aspect of any business or service. Churn is the continuous loss of active users. A low churn rate enables companies to focus more resources on providing better services in contrast to recruiting new users. READ MORE
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17. Evaluating the Viability of Synthetic Pre-training Data for Face Recognition Using a CNN-Based Multiclass Classifier
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Today, face recognition is becoming increasingly accurate and faster with deep learning methods such as convolutional neural networks (CNNs), and is now widely used in areas such as security and entertainment. Typically, these CNNs are trained using real-face datasets like CASIA-WebFace, which was put together using web-crawling of IMDB. READ MORE
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18. Comparing energy efficiency of Leaky integrate-and-fire and Spike response neuron models in Spiking Neural Networks
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Spiking Neural Networks (SNNs) are a type of neural network that is designed to mimic the way neurons function in our brains. While there have been notable advancements in developing SNNs, energy consumption hasn't been studied to the same extent. This gets especially relevant with steadily increasing network sizes. READ MORE
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19. The impact of pruning Convolutional Neural Networks when classifying skin cancer
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Over the past few years, there have been multiple reports showcasing how Convolutional Neural Networks (CNNs) can be used to classify if skin lesions are cancerous or non-cancerous. However, a limitation of CNNs is the large number of parameters resulting in high computation times. READ MORE
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20. On Linear Mode Connectivity up to Permutation of Hidden Neurons in Neural Network : When does Weight Averaging work?
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Neural networks trained using gradient-based optimization methods exhibit a surprising phenomenon known as mode connectivity, where two independently trained network weights are not isolated low loss minima in the parameter space. Instead, they can be connected by simple curves along which the loss remains low. READ MORE
