shape-descriptor

There are 14 repositories under shape-descriptor topic.

  • nipy/mindboggle

    Automated anatomical brain label/shape analysis software (+ website)

    Language:Python1432016054

  • pvnieo/GeomFmaps_pytorch

    A minimalist pytorch implementation of: "Deep Geometric Functional Maps: Robust Feature Learning for Shape Correspondence"

    Language:Python23352

  • jrzaurin/Shoe-Shape-Classifier

    Using the shape context algorithm to classify shoe shapes

    Language:Python223016

  • pvnieo/SURFMNet-pytorch

    A pytorch implementation of: "Unsupervised Deep Learning for Structured Shape Matching"

    Language:Python16462

  • alihashmiii/Elliptical-Fourier-Descriptors

    elliptical fourier descriptors with and without lobe contributions

    Language:Mathematica13314

  • meetps/EE-702

    Project codes for EE702 Computer Vision.

    Language:Python12304

  • bartvbl/libShapeDescriptor

    A library containing GPU implementations of a number of 3D shape descriptors, along with some useful utilities.

    Language:Cuda11233

  • ChesleyTan/bcf

    Python implementation of the Bag of Contour Fragments algorithm for shape classification

    Language:Python9103

  • liu-yikang/SHERM-rodentSkullStrip

    Implementation of algorithm in 'Yikang Liu et al. (2020) Automatic Brain Extraction for Rodent MRI Images. Neuroinformatics. doi: 10.1007/s12021-020-09453-z''

    Language:MATLAB7261

  • Charamba/Cross-Ratio-Arrays-Shape-Descriptor

    Projective invariant shape descriptor based on Cross Ratio Arrays for planar objects recognition like signs and logos

    Language:Python2100

  • 50-Cent/ElasticPath2Path

    Morphological categorization of neurons in order to explore their functional features has drawn significant attention over past few decades. The enormous complexity in the structure of neurons poses a real challenge in the identification and analysis of similar and dissimilar neuronal cells. Existing methodologies often carry out strutural and geometrical simplifications, which substantially changes the morphological statistics. Using digitally-reconstructed neurons, we extend the work of Path2Path as ElasticP2P, which seamlessly integrates the graph-theoretic and differential-geometric frameworks. By decomposing a neuron into a set of paths, we derive graph metrics, which are path concurrence and path hierarchy. Next, we model each path as an elastic string to compute the geodesic distance between the paths of a pair of neurons. Later, we formulate the problem of finding the distance between two neurons as a path assignment problem with a cost function combining the graph metrics and the geodesic deformation of paths.

    Language:MATLAB1100

  • Ayush9719/Segmentation-Based-CBIR

    This is an improved version of basic CBIR for cytological images based on image segmentation

    Language:HTML1100

  • hoffsupes/Galaxy-Counter

    Simple galaxy counter which uses thresholding along with connected components to approximate the count of galaxies in an image

    Language:C++10

  • zeynepturkmen/Digital-Image-Analysis-Assignments

    Sabanci University CS419 (Digital Image and Video Analysis) Assignments

    Language:Jupyter Notebook10