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Showing 6 open source projects for "python projects"
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Detectron2
Next-generation platform for object detection and segmentation
Detectron2 is Facebook AI Research's next generation software system that implements state-of-the-art object detection algorithms. It is a ground-up rewrite of the previous version, Detectron, and it originates from maskrcnn-benchmark. It is powered by the PyTorch deep learning framework. Includes more features such as panoptic segmentation, Densepose, Cascade R-CNN, rotated bounding boxes, PointRend, DeepLab, etc. Can be used as a library to support different projects on top of it. We'll open... -
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StructPie
A set of C libraries to implement data structures and algorithms
Struct-Pie (Structures Pie) is a set of C shared libraries to implement data structures and algorithms so that they can be used/integrated easily into C projects. LIFO & FIFO Stack, Binary Search Tree, Priority Queue and a Hash Table are implemented and included in this package. Future releases will have many other data structures. The hash table in this package uses separate chaining to avoid collision. In the "hash_table" directory, the hash table implementation uses linked lists... -
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DEBay
Deconvolutes qPCR data to estimate cell-type-specific gene expression
... in the sample. The user manual of DEBay: https://sourceforge.net/projects/debay/files/UserManual.pdf Sample data: https://sourceforge.net/projects/debay/files/Test_data/ Citation Information: Vimalathithan Devaraj, Biplab Bose. DEBay: A computational tool for deconvolution of quantitative PCR data for estimation of cell type-specific gene expression in a mixed population. Heliyon, 2020, 6(7), e04489. https://doi.org/10.1016/j.heliyon.2020.e04489 -
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ViennaCL
Linear algebra and solver library using CUDA, OpenCL, and OpenMP
ViennaCL provides high level C++ interfaces for linear algebra routines on CPUs and GPUs using CUDA, OpenCL, and OpenMP. The focus is on generic implementations of iterative solvers often used for large linear systems and simple integration into existing projects. -
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C++, Matlab and Python library for Hidden-state Conditional Random Fields. Implements 3 algorithms: LDCRF, HCRF and CRF. For Windows and Linux, 32- and 64-bits. Optimized for multi-threading. Works with sparse or dense input features.
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Free and easy to implement algorithm that can be used for resource leveling in Gantt projects. Uses resources assignment policies, availibility calendars, tasks\' priorities, dependencies, sizings, complexity due to human communication.
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