Showing 1 open source project for "java image segmentation"

View related business solutions
  • Keep company data safe with Chrome Enterprise Icon
    Keep company data safe with Chrome Enterprise

    Protect your business with AI policies and data loss prevention in the browser

    Make AI work your way with Chrome Enterprise. Block unapproved sites and set custom data controls that align with your company's policies.
    Download Chrome
  • Dun and Bradstreet Risk Analytics - Supplier Intelligence Icon
    Dun and Bradstreet Risk Analytics - Supplier Intelligence

    Use an AI-powered solution for supply and compliance teams who want to mitigate costly supplier risks intelligently.

    Risk, procurement, and compliance teams across the globe are under pressure to deal with geopolitical and business risks. Third-party risk exposure is impacted by rapidly scaling complexity in domestic and cross-border businesses, along with complicated and diverse regulations. It is extremely important for companies to proactively manage their third-party relationships. An AI-powered solution to mitigate and monitor counterparty risks on a continuous basis, this cutting-edge platform is powered by D&B’s Data Cloud with 520M+ Global Business Records and 2B+ yearly updates for third-party risk insights. With high-risk procurement alerts and multibillion match points, D&B Risk Analytics leverages best-in-class risk data to help drive informed decisions. Perform quick and comprehensive screening, using intelligent workflows. Receive ongoing alerts of key business indicators and disruptions.
    Learn More
  • 1
    Jittor

    Jittor

    Jittor is a high-performance deep learning framework

    ...A powerful op compiler and tuner are integrated into Jittor. It allowed us to generate high-performance code specialized for your model. Jittor also contains a wealth of high-performance model libraries, including image recognition, detection, segmentation, generation, differentiable rendering, geometric learning, reinforcement learning, etc. The front-end language is Python. Module Design and Dynamic Graph Execution is used in the front-end, which is the most popular design for deep learning framework interface. The back-end is implemented by high-performance languages, such as CUDA, C++. ...
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next