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  2. 3D reconstruction - Wikipedia

    en.wikipedia.org/wiki/3D_reconstruction

    Machine Learning Based Solutions Machine learning enables learning the correspondance between the subtle features in the input and the respective 3D equivalent. Deep neural networks have shown to be highly effective for 3D reconstruction from a single color image. [15] This works even for non-photorealistic input images such as sketches.

  3. List of programming languages for artificial intelligence

    en.wikipedia.org/wiki/List_of_programming...

    Prolog is particularly useful for symbolic reasoning, database and language parsing applications. Artificial Intelligence Markup Language (AIML) [11] is an XML dialect [12] for use with Artificial Linguistic Internet Computer Entity (A.L.I.C.E.)-type chatterbots. Planner is a hybrid between procedural and logical languages. It gives a ...

  4. 3D reconstruction from multiple images - Wikipedia

    en.wikipedia.org/wiki/3D_Reconstruction_from...

    This method uses X-ray images for 3D Reconstruction and to develop 3D models with low dose radiations in weight bearing positions. In NSCC algorithm, the preliminary step is calculation of an initial solution. Firstly anatomical regions from the generic object are defined. Secondly, manual 2D contours identification on the radiographs is performed.

  5. Triangulation (computer vision) - Wikipedia

    en.wikipedia.org/wiki/Triangulation_(computer...

    x (3D point) is the homogeneous representation of the resulting 3D point. The ∼ {\displaystyle \sim \,} sign implies that τ {\displaystyle \tau \,} is only required to produce a vector which is equal to x up to a multiplication by a non-zero scalar since homogeneous vectors are involved.

  6. Iterative reconstruction - Wikipedia

    en.wikipedia.org/wiki/Iterative_reconstruction

    In learned iterative reconstruction, the updating algorithm is learned from training data using techniques from machine learning such as convolutional neural networks, while still incorporating the image formation model. This typically gives faster and higher quality reconstructions and has been applied to CT [4] and MRI reconstruction. [5]

  7. Tomographic reconstruction - Wikipedia

    en.wikipedia.org/wiki/Tomographic_reconstruction

    One group of deep learning reconstruction algorithms apply post-processing neural networks to achieve image-to-image reconstruction, where input images are reconstructed by conventional reconstruction methods. Artifact reduction using the U-Net in limited angle tomography is such an example application. [6]

  8. List of 3D modeling software - Wikipedia

    en.wikipedia.org/wiki/List_of_3D_modeling_software

    Following is a list of notable software, computer programs, used to develop a mathematical representation of any three dimensional surface of objects, as 3D computer graphics, also called 3D modeling.

  9. List of 3D graphics libraries - Wikipedia

    en.wikipedia.org/wiki/List_of_3D_graphics_libraries

    These APIs for 3D computer graphics are particularly popular: ANGLE, web browsers graphics engine, a cross-platform translator of OpenGL ES calls to DirectX, OpenGL, or Vulkan API calls. Direct3D (a subset of DirectX) Glide a defunct 3D graphics API developed by 3dfx Interactive. Mantle developed by AMD. Metal developed by Apple.