Essays about: "CIFAR-10"
Showing result 11 - 15 of 26 essays containing the word CIFAR-10.
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11. Data augmentation and related opportunity cost for managing the contemporary data sparsity
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : This paper explored data augmentation as an alternative solution to the supervised data sparsity that has become a deeply rooted issue in machine learning projects. Convolutional Neural Network models with architecture resembling the ResNet Neural Network were trained on an augmented version of the CIFAR-10 dataset. READ MORE
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12. Use of Thermal Imagery for Robust Moving Object Detection
University essay from Linköpings universitet/Medie- och Informationsteknik; Linköpings universitet/Tekniska fakultetenAbstract : This work proposes a system that utilizes both infrared and visual imagery to create a more robust object detection and classification system. The system consists of two main parts: a moving object detector and a target classifier. READ MORE
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13. Optimizing Convolutional Neural Networks for Inference on Embedded Systems
University essay from Uppsala universitet/Signaler och systemAbstract : Convolutional neural networks (CNN) are state of the art machine learning models used for various computer vision problems, such as image recognition. As these networks normally need a vast amount of parameters they can be computationally expensive, which complicates deployment on embedded hardware, especially if there are contraints on for instance latency, memory or power consumption. READ MORE
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14. Transfer learning between domains : Evaluating the usefulness of transfer learning between object classification and audio classification
University essay from Högskolan i Skövde/Institutionen för informationsteknologiAbstract : Convolutional neural networks have been successfully applied to both object classification and audio classification. The aim of this thesis is to evaluate the degree of how well transfer learning of convolutional neural networks, trained in the object classification domain on large datasets (such as CIFAR-10, and ImageNet), can be applied to the audio classification domain when only a small dataset is available. READ MORE
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15. Regularization Methods in Neural Networks
University essay from Uppsala universitet/Statistiska institutionenAbstract : Overfitting is a common problem in neural networks. This report uses a simple neural network to do simulations relevant for the field of image recognition. In this report, four common regularization methods for dealing with overfitting are evaluated. READ MORE
