Essays about: "semantic annotations"

Showing result 1 - 5 of 12 essays containing the words semantic annotations.

  1. 1. Aerial View Image-Goal Localization with Reinforcement Learning

    University essay from Lunds universitet/Matematik LTH

    Author : John Backsund; Anton Samuelsson; [2022]
    Keywords : reinforcement learning; UAV; machine learning; policy gradient; artificial intelligence; reinforce; Technology and Engineering;

    Abstract : With an increased amount and availability of unmanned aerial vehicles (UAVs) and other remote sensing devices (e.g. satellites) we have recently seen an explosion in computer vision methodologies tailored towards processing and understanding aerial view data. READ MORE

  2. 2. Classification of Terrain Roughness from Nationwide Data Sources Using Deep Learning

    University essay from Linköpings universitet/Institutionen för systemteknik

    Author : Emily Fredriksson; [2022]
    Keywords : Computer vision; Machine learning; 3D semantic segmentation; Airborne LiDAR data; Terrain classification;

    Abstract : 3D semantic segmentation is an expanding topic within the field of computer vision, which has received more attention in recent years due to the development of more powerful GPUs and the newpossibilities offered by deep learning techniques. Simultaneously, the amount of available spatial LiDAR data over Sweden has also increased. READ MORE

  3. 3. Deep Learning for Earth Observation: improvement of classification methods for land cover mapping : Semantic segmentation of satellite image time series

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

    Author : Benjamin Carpentier; [2021]
    Keywords : Satellite Image Time Series; Remote sensing; Land Cover Classification; Deep Learning; Convolutional Neural Network; Tidsserier av satellitbilder; Fjärranalys; Classificering; Djupinlärning; KonvolutionelltNeuralt Nätverk;

    Abstract : Satellite Image Time Series (SITS) are becoming available at high spatial, spectral and temporal resolutions across the globe by the latest remote sensing sensors. These series of images can be highly valuable when exploited by classification systems to produce frequently updated and accurate land cover maps. READ MORE

  4. 4. Learning from Synthetic Data : Towards Effective Domain Adaptation Techniques for Semantic Segmentation of Urban Scenes

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

    Author : Gerard Valls I Ferrer; [2021]
    Keywords : Semantic Segmentation; Synthetic Data; Autonomous Driving; Domain Shift; Domain Adaptation; Domain Generalisation; Semantisk Segmentering; Syntetiska Data; Autonom Körning; Domänskift; Domänanpassning; Domängeneralisering;

    Abstract : Semantic segmentation is the task of predicting predefined class labels for each pixel in a given image. It is essential in autonomous driving, but also challenging because training accurate models requires large and diverse datasets, which are difficult to collect due to the high cost of annotating images at pixel-level. READ MORE

  5. 5. Training Multi-Task Deep Neural Networks with Disjoint Datasets

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

    Author : Nik Vaessen; [2020]
    Keywords : ;

    Abstract : This work examines training neural networks which are capable of learning multiple tasks. We propose an architecture trained on KITTI and Cityscapes, which respectively include only the annotations for 2D object detection and semantic segmentation. READ MORE