Essays about: "edge machine learning"
Showing result 6 - 10 of 103 essays containing the words edge machine learning.
-
6. Predicting Customer Churn and Customer Lifetime Value (CLV) using Machine Learning
University essay from Lunds universitet/Matematisk statistikAbstract : In an evermore competitive environment for companies and business, predictive customer behaviour models can give companies a competitive edge over its competitors. Two such important predictive behaviour models are customer churn models and customer lifetime value (CLV) models. READ MORE
-
7. Improving Pith Detection and Automated Log Identification using AI
University essay from Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)Abstract : Tracking of tree logs from a harvesting site to its processing site is a legal requirement for timber-based industries. Wood log identification is an important task in the forestry industry and has traditionally relied on manual inspection by trained experts. READ MORE
-
8. Edge Machine Learning for Wildlife Conservation : A part of the Ngulia project
University essay from Linköpings universitet/ReglerteknikAbstract : The prominence of Edge Machine Learning is increasing swiftly as the performance of microcontrollers continues to improve. By deploying object detection and classification models on edge devices with camera sensors, it becomes possible to locate and identify objects in their vicinity. READ MORE
-
9. An experimental analysis of Link Prediction methods over Microservices Knowledge Graphs
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Graphs are a powerful way to represent data. They can be seen as a collection of objects (nodes) and the relationships between them (edges or links). The power of this structure has its intrinsic value in the relationship between data points that can even provide more information than the data properties. READ MORE
-
10. Generating Synthetic Training Data with Stable Diffusion
University essay from Linköpings universitet/Institutionen för datavetenskapAbstract : The usage of image classification in various industries has grown significantly in recentyears. There are however challenges concerning the data used to train such models. Inmany cases the data used in training is often difficult and expensive to obtain. Furthermore,dealing with image data may come with additional problems such as privacy concerns. READ MORE