Essays about: "Classification Guidelines"
Showing result 1 - 5 of 52 essays containing the words Classification Guidelines.
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1. Using GIS and satellite data to assess access of green area for children living in growing cities
University essay from Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskapAbstract : Urban green space (UGS) refers to open spaces within an urban context that are filled with greenery and nature. These can range from very small vegetation to expansive park areas. The common denominator is that they have proven to be beneficial for human health and well-being. Access to green spaces is also important for children. READ MORE
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2. Classifying femur fractures using federated learning
University essay from Linköpings universitet/Statistik och maskininlärningAbstract : The rarity and subtle radiographic features of atypical femoral fractures (AFF) make it difficult to distinguish radiologically from normal femoral fractures (NFF). Compared with NFF, AFF has subtle radiological features and is associated with the long-term use of bisphosphonates for the treatment of osteoporosis. READ MORE
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3. Exploring patterns in risk factors for bark beetle attack during outbreaks triggered by drought stress with harvester data on attacked trees: A case study in Southeastern Sweden
University essay from Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskapAbstract : ABSTRACT Raising temperatures and climate variability have intensified extreme weather events worldwide. These extremes can enhance and trigger possible pest outbreaks. Bark beetle attacks have become a major concern in regions with extensive spruce forest areas. Southeastern Sweden has faced repeated outbreaks resulting in widespread tree loss. READ MORE
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4. Motor Imagery Signal Classification using Adversarial Learning - A Systematic Literature Review
University essay from Stockholms universitet/Institutionen för data- och systemvetenskapAbstract : Context: Motor Imagery (MI) signal classification is a crucial task for developing Brain-Computer Interfaces (BCIs) that allow people to control devices using their thoughts. However, traditional machine learning approaches often suffer from limited performance due to inter-subject variability and limited data availability. READ MORE
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5. A Comparative Study on the Effects of Removing the Most Important Feature on Random Forest and Support Vector Machine
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Machine learning (ML) for classification is largely regarded as a “black box”, in that it’s difficult to fully understand how the model reached a decision, and how changes to the input affects the output. Therefore, exploring the inner workings of classification models are of interest for expanding the current knowledge base, providing guidelines for choosing a more suitable classification model for a specific problem. READ MORE
