Search for dissertations about: "Deep learning semantic"

Showing result 1 - 5 of 31 swedish dissertations containing the words Deep learning semantic.

2. 1. Data-Efficient Learning of Semantic Segmentation

   Author : David Nilsson; Mathematical Imaging Group; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; semantic segmentation; embodied learning; active learning; semantic video segmentation; computer vision; deep learning;

   Abstract : Semantic segmentation is a fundamental problem in visual perception with a wide range of applications ranging from robotics to autonomous vehicles, and recent approaches based on deep learning have achieved excellent performance. However, to train such systems there is in general a need for very large datasets of annotated images. READ MORE

4. 2. Sharing to learn and learning to share : Fitting together metalearning and multi-task learning

   Author : Richa Upadhyay; Marcus Liwicki; Ronald Phlypo; Rajkumar Saini; Atsuto Maki; Luleå tekniska universitet; []
   Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Multi-task learning; Meta learning; transfer learning; knowledge sharing algorithms; Machine Learning; Maskininlärning;

   Abstract : This thesis focuses on integrating learning paradigms that ‘share to learn,’ i.e., Multitask Learning (MTL), and ‘learn (how) to share,’ i.e. READ MORE

5. 3. Multispectral Remote Sensing and Deep Learning for Wildfire Detection

   Author : Xikun Hu; Yifang Ban; Ioannis Gitas; KTH; []
   Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; active fire detection; biome; multi-criteria; Sentinel-2; Landsat-8; burned area mapping; deep learning; semantic segmentation; machine learning.; aktiv branddetektering; biom; multikriterietillvägagångssätt; Sentinel-2; Landsat-8; kartläggning av bränt område; djupinlärning; semantisk segmentering; maskininlärningsmetoderna; Geoinformatik; Geoinformatics;

   Abstract : Remote sensing data has great potential for wildfire detection and monitoring with enhanced spatial resolution and temporal coverage. Earth Observation satellites have been employed to systematically monitor fire activity over large regions in two ways: (i) to detect the location of actively burning spots (during the fire event), and (ii) to map the spatial extent of the burned scars (during or after the event). READ MORE

6. 4. Visual Representations and Models: From Latent SVM to Deep Learning

   Author : Hossein Azizpour; Stefan Carlsson; Barbara Caputo; KTH; []
   Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Computer Vision; Machine Learning; Artificial Intelligence; Deep Learning; Learning Representation; Deformable Part Models; Discriminative Latent Variable Models; Convolutional Networks; Object Recognition; Object Detection; Computer Science; Datalogi;

   Abstract : Two important components of a visual recognition system are representation and model. Both involves the selection and learning of the features that are indicative for recognition and discarding those features that are uninformative. READ MORE

7. 5. Reinforcement Learning for Active Visual Perception

   Author : Aleksis Pirinen; Mathematical Imaging Group; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; computer vision; reinforcement learning; deep learning; active vision; object detection; human pose estimation; semantic segmentation;

   Abstract : Visual perception refers to automatically recognizing, detecting, or otherwise sensing the content of an image, video or scene. The most common contemporary approach to tackle a visual perception task is by training a deep neural network on a pre-existing dataset which provides examples of task success and failure, respectively. READ MORE