Search for dissertations about: "Deep Learning"

Showing result 1 - 5 of 92 swedish dissertations containing the words Deep Learning.

  1. 1. Learner support for distance learners A study of six cases of ICT-based distance education institutions in China

    University dissertation from Stockholm : Department of Education, Stockholm University

    Author : Shuting Gao; Vinayagum Chinapah; Shangwu Zhao; Chang Zhu; [2012]
    Keywords : SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; Learner support; student support; support services; peer support; learner center; collaborative learning; interaction; motivation; critical thinking; creative thinking; deep learning; higher order learning; group learning; small group work; Community of Inquiry CoI ; ICT-based distance learning; Radio and TV University; distance education; Web-based learning; e-Learning; adult education; higher education; International and Comparative Education; internationell och jämförande pedagogik;

    Abstract : This thesis focuses on learner support in Chinese distance education. It draws a picture of Chinese modern distance education, covering the major issues in the field of learner support, and small group work as peer support. READ MORE

  2. 2. Learning and teaching sustainable development in global-local contexts

    University dissertation from Malmö högskola, Fakulteten för lärande och samhälle

    Author : Birgitta Nordén; [2016]
    Keywords : SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; Contextual Analysis; Critical Knowledge Capabilities; Deep approaches to learning; Deep approaches to teaching; Education for Sustainable Development; ESD; Environmental and Sustainabilty Education Research; ESER; Global classrooms; Global learning; Global eduction; Global - local contexts; Global Learning for Sustainable Development; GLSD; Global teaching and learning; Phenomenography; Sustainable Development; SD; sustainability; Teaching Approaches; Transdisciplinary Teaching; Transitions; Transnational education; Online learning; Transnational learning;

    Abstract : The overall aim of this thesis is to develop knowledge of teaching and learning sustainable development in global–local contexts. The research field is global learning for sustainable development (GLSD). READ MORE

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

    University dissertation from Stockholm, Sweden : KTH Royal Institute of Technology

    Author : Hossein Azizpour; Stefan Carlsson; Barbara Caputo; [2016]
    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; Datalogi; Computer Science;

    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

  4. 4. Representation learning for natural language

    University dissertation from Gothenburg : Chalmers tekniska högskola

    Author : Olof Mogren; [2018]
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; artificial neural networks; artificial intelligence; natural language processing; deep learning; machine learning; summarization; representation learning;

    Abstract : Artificial neural networks have obtained astonishing results in a diverse number of tasks. One of the reasons for the success is their ability to learn the whole task at once (endto-end learning), including the representations for data. READ MORE

  5. 5. Deep Learning Applications for Autonomous Driving

    University dissertation from Gothenburg : Chalmers tekniska högskola

    Author : Luca Caltagirone; [2018]
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; sensor fusion; computer vision; deep learning; autonomous driving; robotic perception and planning;

    Abstract : This thesis investigates the usefulness of deep learning methods for solving two important tasks in the field of driving automation: (i) Road detection, and (ii) driving path generation. Road detection was approached using two strategies: The first one considered a bird's-eye view of the driving scene obtained from LIDAR data, whereas the second carried out camera-LIDAR fusion in the camera perspective. READ MORE