Essays about: "kitti"

Showing result 1 - 5 of 28 essays containing the word kitti.

  1. 1. 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

  3. 2. Fault Detection and Diagnosis for Automotive Camera using Unsupervised Learning

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

    Author : Ziyou Li; [2023]
    Keywords : Unsupervised Learning; Autoencoders; Image Clustering; Fault Detection and Diagnosis; Morphological Operations; Hardware-in-Loop; Advanced DriverAssistance System; Oövervakad inlärning; Autoencoders; Bildklustering; Felfindning och Diagnostik; Morfologiska Operationer; Hardware-in-Loop; Avancerade Förarassistanssystem;

    Abstract : This thesis aims to investigate a fault detection and diagnosis system for automotive cameras using unsupervised learning. 1) Can a front-looking wide-angle camera image dataset be created using Hardware-in-Loop (HIL) simulations? 2) Can an Adversarial Autoencoder (AAE) based unsupervised camera fault detection and diagnosis method be crafted for SPA2 Vehicle Control Unit (VCU) using an image dataset created using Hardware-inLoop? 3) Does using AAE surpass the performance of using Variational Autoencoder (VAE) for the unsupervised automotive camera fault diagnosis model? In the field of camera fault studies, automotive cameras stand out for its complex operational context, particularly in Advanced Driver-Assistance Systems (ADAS) applications. READ MORE

  4. 3. Tracking motion in mineshafts : Using monocular visual odometry

    University essay from Umeå universitet/Institutionen för fysik

    Author : Karl Suikki; [2022]
    Keywords : Monocular Visual Odometry; Tracking; ORB; SIFT;

    Abstract : LKAB has a mineshaft trolley used for scanning mineshafts. It is suspended down into a mineshaft by wire, scanning the mineshaft on both descent and ascent using two LiDAR (Light Detection And Ranging) sensors and an IMU (Internal Measurement Unit) used for tracking the position. READ MORE

  5. 4. Deep Visual Inertial-Aided Feature Extraction Network for Visual Odometry : Deep Neural Network training scheme to fuse visual and inertial information for feature extraction

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

    Author : Franco Serra; [2022]
    Keywords : Feature extraction network; Visual Odometry; IMU; Neural Network; Pose estimation; Feature extraction; Visuell Odometri; IMU; Neuralt nätverk; Poseuppskattning;

    Abstract : Feature extraction is an essential part of the Visual Odometry problem. In recent years, with the rise of Neural Networks, the problem has shifted from a more classical to a deep learning approach. This thesis presents a fine-tuned feature extraction network trained on pose estimation as a proxy task. READ MORE

  6. 5. Single image scene-depth estimation based on self-supervised deep learning : For perception in autonomous heavy duty vehicles

    University essay from Uppsala universitet/Avdelningen för visuell information och interaktion

    Author : Yegor Piven; [2021]
    Keywords : computer vision; machine learning; deep learning; depth estimation; single image depth estimation;

    Abstract : Depth information is a vital component for perception of the 3D structure of vehicle's surroundings in the autonomous scenario. Ubiquity and relatively low cost of camera equipment make image-based depth estimation very attractive compared to employment of the specialised sensors. READ MORE