Essays about: "data augmentation"
Showing result 36 - 40 of 179 essays containing the words data augmentation.
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36. Improving Soil Information with Generative and Machine Learning Models
University essay from Göteborgs universitet/Institutionen för data- och informationsteknikAbstract : Soil data observations are among the most difficult data to collect. Low sample density along with the high cost of sampling has made current soil information that are usually presented as maps, unusable for detailed applications such as modelling earth system dynamics, crop modelling, natural hazards prediction and climate change impacts. READ MORE
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37. Investigation of Facial Age Estimation using Deep Learning
University essay from Uppsala universitet/Institutionen för informationsteknologiAbstract : Age estimation from facial images has drawn increasing attention in the past fewyears. This thesis project performs the age group classification of facial imagesacquired in in-the-wild conditions using deep convolutional neural networkstechniques. READ MORE
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38. Machine learning assisted decision support system for image analysis of OCT
University essay from Luleå tekniska universitet/Institutionen för system- och rymdteknikAbstract : Optical Coherence Tomography (OCT) has been around for more than 30 years and is still being continuously improved. The department of ophthalmology is a part of Sahlgrenska Hospital that heavily uses OCT for helping people with the treatment of eye diseases. READ MORE
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39. Automatic text placement on maps using deep learning keypoint detection models
University essay from Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskapAbstract : Labeling the map is one of the most essential parts of the cartographic process that requires a huge time and energy. It is proven that the automation of map labeling is an NP-hard problem. There have been many research studies that tried to solve it such as rule-based methods, metaheuristics, and integer programming. READ MORE
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40. Deep neural networks for food waste analysis and classification : Subtraction-based methods for the case of data scarcity
University essay from Uppsala universitet/Signaler och systemAbstract : Machine learning generally requires large amounts of data, however data is often limited. On the whole the amount of data needed grows with the complexity of the problem to be solved. Utilising transfer learning, data augmentation and problem reduction, acceptable performance can be achieved with limited data for a multitude of tasks. READ MORE
