Essays about: "Syntetiskt dataset"

Showing result 1 - 5 of 14 essays containing the words Syntetiskt dataset.

  1. 1. 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

  3. 2. Biases in AI: An Experiment : Algorithmic Fairness in the World of Hateful Language Detection

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

    Author : Anna Stozek; [2023]
    Keywords : machine learning; algorithmic fairness; unintended bias; sentiment analysis; automated hate detection; maskininlärning; algoritmisk rättvisa; oavsiktlig bias; sentimentanalys; automatisk hatdetektion;

    Abstract : Hateful language is a growing problem in digital spaces. Human moderators are not enough to eliminate the problem. Automated hateful language detection systems are used to aid the human moderators. One of the issues with the systems is that their performance can differ depending on who is the target of a hateful text. READ MORE

  4. 3. Domain Adaptation Of Front View Synthetic Point Clouds Using GANs For Autonomous Driving

    University essay from KTH/Väg- och spårfordon samt konceptuell fordonsdesign

    Author : Friedemann Kleinsteuber; [2023]
    Keywords : LiDAR; Domain Adaptation; GAN; CycleGAN; Simulation; LiDAR; Domänadaption; GAN; CycleGAN; Simulation;

    Abstract : The perception of the environment is one of the main enablers of Autonomous Driving and is driven by Cameras, RADAR, and LiDAR sensors. Deep Learning algorithms used in perception need a vast amount of labeled, high-quality data which is costly to obtain for LiDAR sensors. READ MORE

  5. 4. Multi-factor approximation : An analysis and comparison ofMichael Pykhtin's paper “Multifactor adjustment”

    University essay from Umeå universitet/Institutionen för matematik och matematisk statistik

    Author : Michael Zanetti; Philip Güzel; [2023]
    Keywords : Credit risk; Value at Risk; Expected Shortfall; Monte Carlo simulation; Advanced Internal Rantings-Based models; Kreditrisk; Value at Risk; Expected Shortfall; Monte Carlo simulation; Advanced Internal Rantings-Based-modeller;

    Abstract : The need to account for potential losses in rare events is of utmost importance for corporations operating in the financial sector. Common measurements for potential losses are Value at Risk and Expected Shortfall. These are measures of which the computation typically requires immense Monte Carlo simulations. READ MORE

  6. 5. Evaluating Transfer Learning Models on Synthetic Data for Beverage Label Image Retrieval : A Comparative Study

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

    Author : Anton Brask; [2022]
    Keywords : ;

    Abstract : Information retrieval is a research area that has seen improvements with the development of deep learning and artificial neural networks. The vast amount of image data available today has made it possible to train computer vision models for efficient image search. READ MORE