Sökning: "Pedestrian model evaluation"
Visar resultat 1 - 5 av 15 uppsatser innehållade orden Pedestrian model evaluation.
1. Comparison and performance analysis of deep learning techniques for pedestrian detection in self-driving vehicles
Kandidat-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskapSammanfattning : Background: Self-driving cars, also known as automated cars are a form of vehicle that can move without a driver or human involvement to control it. They employ numerous pieces of equipment to forecast the car’s navigation, and the car’s path is determined depending on the output of these devices. LÄS MER
2. Vibrations in a high frequency clt floor panel - Measurement, prediction and evaluation
Uppsats för yrkesexamina på avancerad nivå, Lunds universitet/Byggnadsmekanik; Lunds universitet/Institutionen för byggvetenskaperSammanfattning : There is an increased need for floors that can accommodate different type of sensitive equipment [1]. Further, it is recommended to design these floors as high frequency floors (HFF) to be able to meet the stringent vibration criteria [1]. LÄS MER
3. Radar Detection Using Deep Learning
Master-uppsats, Lunds universitet/Matematik LTHSammanfattning : This thesis aims to reproduce and improve a paper about dynamic road user detection on 2D bird's-eye-view radar point cloud in the context of autonomous driving. We choose RadarScenes, a recent large public dataset, to train and test deep neural networks. LÄS MER
4. Från trafikled till stadsstråk : en utvärdering av Råbyvägen i Uppsala kommun
Kandidat-uppsats, SLU/Dept. of Urban and Rural DevelopmentSammanfattning : Då bilen blev allt vanligare i Sverige från 1950-talet förändrades stadsplaneringsidealen från fokus på människans till bilens framkomlighet. Efter millennieskiftet har idealen börjat vända igen och städer står nu inför utmaningen att anpassas både för människor och fordon. LÄS MER
5. Estimating Position and Velocity of Traffic Participants Using Non-Causal Offline Algorithms
Master-uppsats, Linköpings universitet/ReglerteknikSammanfattning : In this thesis several non-causal offline algorithms are developed and evaluated for a vision system used for pedestrian and vehicle traffic. The reason was to investigate if the performance increase of non-causal offline algorithms alone is enough to evaluate the performance of vision system. LÄS MER