Sökning: "Traffic Sign Classification"

Visar resultat 1 - 5 av 10 uppsatser innehållade orden Traffic Sign Classification.

1. 1. Generation of Synthetic Traffic Sign Images using Diffusion Models

   Master-uppsats, Linköpings universitet/Datorseende

   Författare :Johanna Carlson; Lovisa Byman; [2023]
   Nyckelord :Machine Learning; Computer Vision; Diffusion Models; Traffic Sign Recognition; Traffic Sign Classification; Synthetic Data; Maskininlärning; Datorseende; Diffusionsmodeller; Trafikskyltsigenkänning; Trafikskyltsklassificering; Syntetisk data;

   Sammanfattning : In the area of Traffic Sign Recognition (TSR), deep learning models are trained to detect and classify images of traffic signs. The amount of data available to train these models is often limited, and collecting more data is time-consuming and expensive. LÄS MER

3. 2. A Deep Learning Application for Traffic Sign Recognition

   Kandidat-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskap

   Författare :Pramod Sai Kondamari; Anudeep Itha; [2021]
   Nyckelord :Image Processing; Deep Learning Algorithms; Convolutional Neural Network CNN ; OpenCV; Supervised Learning.;

   Sammanfattning : Background: Traffic Sign Recognition (TSR) is particularly useful for novice driversand self-driving cars. Driver Assistance Systems(DAS) involves automatic trafficsign recognition. Efficient classification of the traffic signs is required in DAS andunmanned vehicles for safe navigation. LÄS MER

4. 3. Traffic Sign Classification Using Computationally Efficient Convolutional Neural Networks

   Master-uppsats, Linköpings universitet/Datorseende

   Författare :Carl Ekman; [2019]
   Nyckelord :CNN; Machine Learning; Deep Learning; Computer Vision; Traffic Sign Recognition; Traffic Sign Classification; Image Classification; Neural Networks;

   Sammanfattning : Traffic sign recognition is an important problem for autonomous cars and driver assistance systems. With recent developments in the field of machine learning, high performance can be achieved, but typically at a large computational cost. LÄS MER

5. 4. An Analysis of Cloud-Based Machine Learning Models for Traffic-Sign Classification

   Master-uppsats, Linköpings universitet/Kommunikations- och transportsystem; Linköpings universitet/Tekniska fakulteten

   Författare :Victor Lindeman; [2019]
   Nyckelord :machine learning traffic signcloud;

   Sammanfattning : The machine learning method deep neural networks are commonly used for artificial intelligence applications such as speech recognition, robotics, and computer vision. Deep neural networks often have very good accuracy, the downside is the complexity of the computations. LÄS MER

7. 5. Autonomous Driving: Traffic Sign Classification

   Master-uppsats, Blekinge Tekniska Högskola/Institutionen för tillämpad signalbehandling

   Författare :Sai Subhakar Tirumaladasu; Shirdi Manjunath Adigarla; [2019]
   Nyckelord :Autonomous Driving; Deep Learning; Image Processing; Convolutional Neural Networks; Recurrent Neural Networks; Generative Adversarial Networks;

   Sammanfattning : Autonomous Driving and Advance Driver Assistance Systems (ADAS) are revolutionizing the way we drive and the future of mobility. Among ADAS, Traffic Sign Classification is an important technique which assists the driver to easily interpret traffic signs on the road. LÄS MER