2 projects for "python data analysis" with 2 filters applied:

  • AestheticsPro Medical Spa Software Icon
    AestheticsPro Medical Spa Software

    Our new software release will dramatically improve your medspa business performance while enhancing the customer experience

    AestheticsPro is the most complete Aesthetics Software on the market today. HIPAA Cloud Compliant with electronic charting, integrated POS, targeted marketing and results driven reporting; AestheticsPro delivers the tools you need to manage your medical spa business. It is our mission To Provide an All-in-One Cutting Edge Software to the Aesthetics Industry.
    Learn More
  • OpenMetal is an automated bare metal and on-demand private cloud provider. Icon
    OpenMetal is an automated bare metal and on-demand private cloud provider.

    Large Scale. Cloud Native. Fixed Costs.

    OpenMetal is an automated bare metal and on-demand private cloud provider. Our mission is to empower your team with cost effective private infrastructure that outperforms traditional public cloud.
    Learn More
  • 1
    Detic

    Detic

    Code release for "Detecting Twenty-thousand Classes

    Detic (“Detecting Twenty-thousand Classes using Image-level Supervision”) is a large-vocabulary object detector that scales beyond fully annotated datasets by leveraging image-level labels. It decouples localization from classification, training a strong box localizer on standard detection data while learning classifiers from weak supervision and large image-tag corpora. A shared region proposal backbone feeds a flexible classification head that can expand to tens of thousands of categories...
    Downloads: 0 This Week
    Last Update:
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  • 2
    VoteNet

    VoteNet

    Deep Hough Voting for 3D Object Detection in Point Clouds

    VoteNet is a 3D object detection framework for point clouds that combines deep point set networks with a Hough voting mechanism to localize and classify objects in 3D space. It tackles the challenge that object centroids in 3D scenes often don’t lie on any input surface point by having each point “vote” for potential object centers; these votes are then clustered to propose object hypotheses. Once cluster centers are formed, the network regresses bounding boxes around them and classifies...
    Downloads: 1 This Week
    Last Update:
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