Sökning: "Metric Learning"
Visar resultat 1 - 5 av 180 uppsatser innehållade orden Metric Learning.
1. Investigating the Accuracy of Metric-Based versus Machine Learning Approaches in Detecting Design Patterns
Kandidat-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknikSammanfattning : Design pattern detection approaches have evolved, with machine-learning methods gaining prominence. However, implementing machine-learning models can be challenging due to extensive training requirements and the need for large labeled design pattern datasets. LÄS MER
2. Preserving Privacy in Cloud Services by Using an Explainable Deep-Learning Model for Anomaly Detection
Master-uppsats, Linköpings universitet/Institutionen för datavetenskapSammanfattning : As cloud services become increasingly popular, ensuring their privacy and security has become a significant concern for users. Cloud computing involves Data Service Outsourcing and Computation Outsourcing, which require additional security considerations compared to traditional computing. LÄS MER
3. Biodiversity Monitoring Using Machine Learning for Animal Detection and Tracking
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : As an important indicator of biodiversity and ecological environment in a region, the number and distribution of animals has been given more and more attention by agencies such as nature reserves, wetland parks, and animal protection supervision departments. To protect biodiversity, we need to be able to detect and track the movement of animals to understand which animals are visiting the space. LÄS MER
4. Mapping of Dependent Structural Responses on a Prestressed Concrete Bridge using Machine Learning Regression Analysis and Historical Data : A Comparison of Different Non-linear Regression Approaches
L1-uppsats, Umeå universitet/Institutionen för datavetenskapSammanfattning : Prestressed concrete bridges are susceptible to deterioration over time which might significantly affect their capacity and overall performance. In previous decades, infrastructure owners have found that continuous monitoring of these assets is a valuable tool for their management as it facilitates the decision-making process regarding the intervention strategies required. LÄS MER
5. Study of evaluation metrics while predicting the yield of lettuce plants in indoor farms using machine learning models
Magister-uppsats, Högskolan i Skövde/Institutionen för informationsteknologiSammanfattning : A key challenge for maximizing the world’s food supply is crop yield prediction. In this study, three machine models are used to predict the fresh weight (yield) of lettuce plants that are grown inside indoor farms hydroponically using the vertical farming infrastructure, namely, support vector regressor (SVR), random forest regressor (RFR), and deep neural network (DNN). LÄS MER