Essays about: "Object of learning"

Showing result 21 - 25 of 462 essays containing the words Object of learning.

  1. 21. Comparison and performance analysis of deep learning techniques for pedestrian detection in self-driving vehicles

    University essay from Blekinge Tekniska Högskola/Institutionen för datavetenskap

    Author : Raahitya Botta; Aditya Aditya; [2023]
    Keywords : Artificial Intelligence AI ; Dataset; Deep learning; Object detection; Pedestrian detection; Performance analysis; Self-driving vehicles.;

    Abstract : 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. READ MORE

  2. 22. Data Augmentations for Improving Vision-Based Damage Detection : in Land Transport Infrastructure

    University essay from KTH/Lantmäteri – fastighetsvetenskap och geodesi

    Author : Punnawat Siripatthiti; [2023]
    Keywords : Computer Vision; Data Augmentation; Object Detection; Crack Detection; Road Damage Detection; Sleeper Defect Detection; datorseende; dataökning; objektdetektering; sprickdetektering; vägbeläggning; järnvägsslipers;

    Abstract : Crack, a typical term most people know, is a common form of distress or damage in road pavements and railway sleepers. It poses significant challenges to their structural integrity, safety, and longevity. Over the years, researchers have developed various data-driven technologies for image-based crack detection in road and sleeper applications. READ MORE

  3. 23. LiDAR Perception in a Virtual Environment Using Deep Learning : A comparative study of state-of-the-art 3D object detection models on synthetic data

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Samuel Skoog; [2023]
    Keywords : Object Detection; LiDAR; CARLA; Deep Learning; Autonomous Vehicles; Objektdetektering; LiDAR; CARLA; Djupinlärning; Autonoma fordon;

    Abstract : Perceiving the environment is a crucial aspect of autonomous vehicles. To plan the route, the autonomous vehicle needs to be able to detect objects such as cars and pedestrians. This is possible through 3D object detection. However, labeling this type of data is time-consuming. READ MORE

  4. 24. Scene Reconstruction From 4D Radar Data with GAN and Diffusion : A Hybrid Method Combining GAN and Diffusion for Generating Video Frames from 4D Radar Data

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Alexandr Djadkin; [2023]
    Keywords : Deep generative models; Generative adversarial networks; Diffusion models; GAN; DGM; 4D imaging radar; Djupa generativa modeller; Generativa antagonistiska nätverk; Diffusionsmodeller; GAN; DGM; 4D-bildradar;

    Abstract : 4D Imaging Radar is increasingly becoming a critical component in various industries due to beamforming technology and hardware advancements. However, it does not replace visual data in the form of 2D images captured by an RGB camera. READ MORE

  5. 25. Multi-Scale Task Dynamics in Transfer and Multi-Task Learning : Towards Efficient Perception for Autonomous Driving

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Simon Ekman von Huth; [2023]
    Keywords : Autonomous Driving; Computer Vision; Deep Learning; Machine Learning; Multi-Task Learning; Transfer Learning; Task Relationships; Task Dynamics; Python; Multi-Scale Representation Learning; Fuss-Free Network; Självkörande Fordon; Datorseende; Djupinlärning; Maskininlärning; Multiuppgiftsinlärning; Överföringsinlärning; Uppgiftsrelationer; Uppgiftsdynamik; Python; Flerskalig Representationsinlärning; Fuss-Free Nätverk;

    Abstract : Autonomous driving technology has the potential to revolutionize the way we think about transportation and its impact on society. Perceiving the environment is a key aspect of autonomous driving, which involves multiple computer vision tasks. READ MORE