Showing 2 open source projects for "php-java-bridge"

View related business solutions
  • AI Powered Global HCM for the Evolving World of Work Icon
    AI Powered Global HCM for the Evolving World of Work

    For Start-ups, SME's, Large Enterprise

    Darwinbox is a new-age & disruptive mobile-first, cloud-based HRMS platform built for the large enterprises to attract, engage and nurture their most critical resource - talent. It is an end-to-end integrated HR system that aids in streamlining activities across the employee lifecycle (Hire to Retire). Our powerful enterprise product features are built with a clear focus on intuitiveness and scalability, with standards of best in class consumer apps. Darwinbox’s motto is to engage, empower, and inspire employees on one side in addition to automating and simplifying all HR processes for the enterprise on the other. Over 350+ leading enterprises with 850k users manage their entire employee lifecycle on this unified platform.
    Learn More
  • Enterprise AI Agents for Every Customer Moment Icon
    Enterprise AI Agents for Every Customer Moment

    For enterprise companies looking for AI Agents

    From chat to voice to SMS, every conversation gets a smart, personalized response powered by your policies, tone, and data.
    Learn More
  • 1
    OpenCV

    OpenCV

    Open Source Computer Vision Library

    The Open Source Computer Vision Library has >2500 algorithms, extensive documentation and sample code for real-time computer vision. It works on Windows, Linux, Mac OS X, Android, iOS in your browser through JavaScript. Languages: C++, Python, Julia, Javascript Homepage: https://opencv.org Q&A forum: https://forum.opencv.org/ Documentation: https://docs.opencv.org Source code: https://github.com/opencv Please pay special attention to our tutorials!...
    Leader badge
    Downloads: 3,016 This Week
    Last Update:
    See Project
  • 2
    ConvNeXt

    ConvNeXt

    Code release for ConvNeXt model

    ...It revisits classic ResNet-style backbones through the lens of transformer design trends—large kernel sizes, inverted bottlenecks, layer normalization, and GELU activations—to bridge the performance gap between convolutions and attention-based models. ConvNeXt’s clean, hierarchical structure makes it efficient for both pretraining and fine-tuning across a wide range of visual recognition tasks. It achieves competitive or superior results on ImageNet and downstream datasets while being easier to deploy and train than transformers. ...
    Downloads: 1 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next
MongoDB Logo MongoDB