Essays about: "using computer in class"
Showing result 1 - 5 of 63 essays containing the words using computer in class.
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1. Generation of Synthetic Traffic Sign Images using Diffusion Models
University essay from Linköpings universitet/DatorseendeAbstract : 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. READ MORE
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2. Drone Detection using Deep Learning
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Drone intrusions have been reported more frequently these years as drones become more accessible in the market. The abuse of drones puts threats to public and individual safety and privacy. Traditional anti-drone systems use radio-frequency sensors widely to get the position of drones. READ MORE
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3. Fog detection using an artificial neural network
University essay from Lunds universitet/Matematisk statistikAbstract : This project studies a method of image-based fog detection directly from a camera without using the transmissometer. Fog can be detected using transmissometers which could be a very costly approach. This thesis presents an image-based approach for fog detection using Artificial Neural networks. READ MORE
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4. Unsupervised Domain Adaptation for 3D Object Detection Using Adversarial Adaptation : Learning Transferable LiDAR Features for a Delivery Robot
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : 3D object detection is the task of detecting the full 3D pose of objects relative to an autonomous platform. It is an important perception system that can be used to plan actions according to the behavior of other dynamic objects in an environment. READ MORE
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5. Computer Vision-Based Dangerous Riding Behaviors Detection
University essay from Uppsala universitet/Institutionen för informationsteknologiAbstract : This study addresses the need for detecting dangerous riding behaviors in the context of e-scooters. The research focuses on developing object detection and image classification models to identify dangerous rides, particularly instances where multiple people ride on a single e-scooter simultaneously. READ MORE