Navan.ai is a no code platform for building computer vision models. It allows users to train and deploy computer vision models without the need to write any code.
To use Navan.ai, follow these steps: 1. Sign up for an account on the website. 2. Choose a template for your computer vision model. 3. Upload your images and train the model with just a few clicks. 4. Test the performance of your model using nStudio. 5. Export the model files or deploy the model using an API.
More Contact, visit the contact us page(https://navan.ai/contact-us)
navan.ai Company name: Navan AI Pte Ltd. A Saaragh Technologies Company .
navan.ai Company address: 60 Paya Lebar Road, 06-01 Paya Lebar Square, Singapore 409051.
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Navan: Computer Vision AI
Docker AI/ML Hackathon 2023: Navan Workshop Build computer vision AI models in minutes and deploy seamlessly using Docker. Navan.ai is a no-code platform enabling AI and non-AI developers to build and deploy computer vision models in minutes with just a few clicks."
Pothole Detection Solution using AI Vision / Computer Vision by navan.ai
navan.ai is an AI, Generative AI, and LLM solutions company headquartered in Singapore with offices in India and partners globally. This is a demo video showing our computer vision model trained to detect cracks, potholes and a few other objects on roads using AI. If you have similar requirements, please reach us on connect@navan.ai to discuss how we can help you use AI to automate detection of various objects, actions, and people in images and videos at scale. #ai #potholes #generativeai #computervision #llm #videoanalytics
How to build a Vehicle Classification Computer Vision AI Model?
https://navan.ai is platform enabling developers to build and deploy computer vision AI models without writing a single line of code. This video shows you how you can build a computer vision AI model which can classify between different types of vehicles using https://navan.ai Here are some examples of where this model can be used: 1. To understand road usage patterns and plan the network of roadways: The width of the roads required can be calculated by looking at the type of vehicles traveling by that road. 2. To ensure sustainability: Governments can calculate the estimated pollution levels and carbon footprint to come up with solutions to tackle the pollution. 3. Can be used at toll gates: Toll collectors can use such a computer vision model to automatically classify the type of the vehicle and charge the relevant amount of toll. To know more about the use cases of this model, check out the entire video. To get a step-by-step guide on how to build such a model, visit https://navan.ai/blog/no-code-computer-vision-ai-vehicle-classification Have you used such a model in any of your applications to classify different types of vehicles? Share your ideas and use cases in the comments. Want to build your own computer vision AI model without writing a single line of code? Get started for FREE on https://navan.ai #ai #computervision #code #developers #ml
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