C library for reading virtual slide images
- pathology
- whole-slide-imaging
- c
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C library for reading virtual slide images
A Python native dynamical system simulation framework in the block diagram paradigm.
Large collection of number systems providing custom arithmetic for mixed-precision algorithm development and optimization for AI, Machine Learning, Computer Vision, Signal Processing, CAE, EDA, control, optimization, estimation, and approximation.
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The fastest automatic differentiation library for C++, with Python bindings. Forward, adjoint and higher-order derivatives, checkpointing, Eigen support and JIT. Reproducible benchmarks against CppAD, Adept and autodiff.
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A C/C++ header file for fast 32-bit division remainders (and divisibility tests) on 64-bit hardware.
Collection of self-contained header-only libraries for C++17
The universe in numbers. Free, open-source calculators for everything countable.
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Kaapana is an open source toolkit for state of the art platform provisioning in the field of medical data analysis. The applications comprise AI-based workflows and federated learning scenarios with a focus on radiological and radiotherapeutic imaging. The name Kaapana comes from the Hawaiian word kaʻāpana, meaning "distributor" or "part".
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Cancer Imaging Phenomics Toolkit (CaPTk) is a software platform to perform image analysis and predictive modeling tasks. Documentation: https://cbica.github.io/CaPTk