Showing 6 open source projects for "calculate"

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  • 1
    SAHI

    SAHI

    A lightweight vision library for performing large object detection

    A lightweight vision library for performing large-scale object detection & instance segmentation. Object detection and instance segmentation are by far the most important fields of applications in Computer Vision. However, detection of small objects and inference on large images are still major issues in practical usage. Here comes the SAHI to help developers overcome these real-world problems with many vision utilities. Detection of small objects and objects far away in the scene is a major...
    Downloads: 0 This Week
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  • 2
    GNNPCSAFT

    GNNPCSAFT

    Smart Thermodynamic Modeling with Graph Neural Networks

    The GNNPCSAFT app is an implementation of our project that focuses on using Graph Neural Networks (GNN) to estimate the pure-component parameters of the Equation of State PC-SAFT. We developed this app so the scientific community can access the model's results easily. In this app, the estimated pure-component parameters can be used to calculate thermodynamic properties and compare them with experimental data from the ThermoML Archive. To install the GNNPCSAFT app, download the appropriate latest release from the Files, unzip the file, and run the executable for your operating system (Linux or Windows). More info on github repository.
    Downloads: 0 This Week
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  • 3
    GNNPCSAFT Web App

    GNNPCSAFT Web App

    Smart Thermodynamic Modeling with Graph Neural Networks

    The GNNPCSAFT Web App is an implementation of our project that focuses on using Graph Neural Networks (GNN) to estimate the pure-component parameters of the Equation of State PC-SAFT. We developed this app so the scientific community can access the model's results easily. In this app, the estimated pure-component parameters can be used to calculate thermodynamic properties and compare them with experimental data from the ThermoML Archive. More info on github repository.
    Downloads: 0 This Week
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  • 4
    mAP

    mAP

    Evaluates the performance of your neural net for object recognition

    In practice, a higher mAP value indicates a better performance of your neural net, given your ground truth and set of classes. The performance of your neural net will be judged using the mAP criteria defined in the PASCAL VOC 2012 competition. We simply adapted the official Matlab code into Python (in our tests they both give the same results). First, your neural net detection-results are sorted by decreasing confidence and are assigned to ground-truth objects. We have "a match" when they...
    Downloads: 0 This Week
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  • 5

    Unsupervised Random Forest

    On-line Unsupervised Random Forest

    This tool uses Random Forest and PAM to cluster observations and to calculate the dissimilarity between observations. It supports on-line prediction of new observations (no need to retrain); and supports datasets that contain both continuous (e.g. CPU load) and categorical (e.g. VM instance type) features. In particular, we use an unsupervised formulation of the Random Forest algorithm to calculate similarities and provide them as input to a clustering algorithm.
    Downloads: 0 This Week
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  • 6
    HoldemAI

    HoldemAI

    Texas Holdem Poker AI

    Full ring Texas Hold'em poker game built around an intelligent AI system. The AI uses players' betting actions to calculate a probability distribution of their hole cards and uses it to evaluate hand strength and the best possible action. Small random changes are made to mimic human behavior and make the AI less predictable. Future versions will include adaptive opponent modeling using neural networks to improve the AI's strength. The AI code can be easily adapted for input from screen scrapers.
    Downloads: 0 This Week
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