Browsing Fakultät für Bauingenieurwesen und Geodäsie by Author "d5567d9e-06c9-43ff-892f-c7a0df6af83c"

Browsing Fakultät für Bauingenieurwesen und Geodäsie by Author "d5567d9e-06c9-43ff-892f-c7a0df6af83c"

Sort by: Order: Results:

  • Feature descriptor by convolution and pooling autoencoders 
    Chen, Lin; Rottensteiner, Franz; Heipke, Christian (Göttingen : Copernicus GmbH, 2015)
    In this paper we present several descriptors for feature-based matching based on autoencoders, and we evaluate the performance of these descriptors. In a training phase, we learn autoencoders from image patches extracted ...
  • Feature detection and description for image matching: from hand-crafted design to deep learning 
    Chen, Lin; Rottensteiner, Franz; Heipke, Christian (Wuhan : Wuhan Univ. Journals Press, 2020)
    In feature based image matching, distinctive features in images are detected and represented by feature descriptors. Matching is then carried out by assessing the similarity of the descriptors of potentially conjugate ...
  • GATraj: A graph- and attention-based multi-agent trajectory prediction model 
    Cheng, Hao; Liu, Mengmeng; Chen, Lin; Broszio, Hellward; Sester, Monika; Yang, Michael Ying (Amsterdam [u.a.] : Elsevier, 2023)
    Trajectory prediction has been a long-standing problem in intelligent systems like autonomous driving and robot navigation. Models trained on large-scale benchmarks have made significant progress in improving prediction ...
  • Improving disparity estimation based on residual cost volume and reconstruction error volume 
    Kang, Junhua; Chen, Lin; Deng, Fei; Heipke, Christian (Katlenburg-Lindau : Copernicus Publications, 2020)
    Recently, great progress has been made in formulating dense disparity estimation as a pixel-wise learning task to be solved by deep convolutional neural networks. However, most resulting pixel-wise disparity maps only show ...
  • Invariant descriptor learning using a Siamese convolutional neural network 
    Chen, Lin; Rottensteiner, Franz; Heipke, Christian (Göttingen : Copernicus GmbH, 2016)
    In this paper we describe learning of a descriptor based on the Siamese Convolutional Neural Network (CNN) architecture and evaluate our results on a standard patch comparison dataset. The descriptor learning architecture ...
  • Learning image descriptors for matching based on Haar features 
    Chen, Lin; Rottensteiner, Franz; Heipke, Christian (Göttingen : Copernicus GmbH, 2014)
    This paper presents a new and fast binary descriptor for image matching learned from Haar features. The training uses AdaBoost; the weak learner is built on response function for Haar features, instead of histogram-type ...

Search the repository


Browse

My Account

Usage Statistics