Sökning: "d uppsats datavetenskap"
Visar resultat 1 - 5 av 8 uppsatser innehållade orden d uppsats datavetenskap.
1. Design of a 2-D Lattice Flower Constellation for Earth observation applying the twin satellite concept
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Events such as forest fires or floods are a danger to our Earth’s environment and the people living in it. The sooner they can be detected, the less damage they can cause. An idea arises: use satellites to monitor the Earth and relay information to prevention and rescue organizations in a very short time, regardless of accessibility from ground. LÄS MER
2. Robust light source detection for AUV docking
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : For Autonomous Underwater Vehicles (AUVs) to be able to conduct longterm surveys, the ability to return to a docking station for maintenance and recharging is crucial. A dynamic docking system where a slowly moving submarine acts as the docking station provides increased hydrodynamic control and reduces the impact of environmental disturbances. LÄS MER
3. Design of a Dielectric Radome using a Ray-Tracing Model for Satellite Communications
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : In recent years, there has been a huge increase in the use of satellite communications. This has led to a need for more capacity, which can be solved by moving towards higher frequency bands in search of higher bandwidths. LÄS MER
4. The ghost in the machine : Exploring the impact of noise in datasets used for graph-based action recognition
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Human action recognition is the task of classifying human movement and actions from video data. To benchmark different algorithms within the action recognition field, a common benchmark dataset, called NTU-RGB+D is used. However, this dataset is not without its issues as some samples contain data that is mistakenly captured as a human. LÄS MER
5. An investigation of categorical variable encoding techniques in machine learning: binary versus one-hot and feature hashing
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Machine learning methods can be used for solving important binary classification tasks in domains such as display advertising and recommender systems. In many of these domains categorical features are common and often of high cardinality. LÄS MER
