Essays about: "CIFAR10"
Showing result 1 - 5 of 10 essays containing the word CIFAR10.
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1. Building a Deep Neural Network From Scratch
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Machine learning is becoming increasingly common in our society and is predictedto have a major impact in the future. Therefore, it would be both interesting and valuable tohave a deep understanding of one of the most used algorithms in machine learning, deepneural network. READ MORE
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2. Basil-GAN
University essay from KTH/Matematisk statistikAbstract : Developments in computer vision has sought to design deep neural networks which trained on a large set of images are able to generate high quality artificial images which share semantic qualities with the original image set. A pivotal shift was made with the introduction of the generative adversarial network (GAN) by Goodfellow et al.. READ MORE
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3. Deep Active Learning for Image Classification using Different Sampling Strategies
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Convolutional Neural Networks (CNNs) have been proved to deliver great results in the area of computer vision, however, one fundamental bottleneck with CNNs is the fact that it is heavily dependant on the ground truth, that is, labeled training data. A labeled dataset is a group of samples that have been tagged with one or more labels. READ MORE
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4. Attractors of autoencoders : Memorization in neural networks
University essay from Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)Abstract : It is an important question in machine learning to understand how neural networks learn. This thesis sheds further light onto this by studying autoencoder neural networks which can memorize data by storing it as attractors. READ MORE
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5. Comparing Catastrophic Interference between Incremental Moment Matching-Mean and Hard Attention to the Task
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : When a neural networks trained on data to solve one problem is trained on new data to solve another problem it tends to forget what it had previously knew that made it able to solve the first problem. This phenomenon is called Catastrophic Interference. READ MORE