Computer vision projects kaggle

  • How to do projects on Kaggle?

    A general strategy

    1. Create a dataset comprised of annotated images or use an existing one
    2. Extract, from each image, features pertinent to the task at hand
    3. Train a deep learning model based on the features isolated
    4. Evaluate the model using images that weren't used in the training phase

  • What does kaggle offer?

    In addition to competitions, Kaggle also offers public data sets, machine learning notebooks, and tutorials to help users learn and practice their skills in data science and machine learning..

  • What is a kaggle project?

    A subsidiary of Google, it is an online community of data scientists and machine learning engineers.
    Kaggle allows users to find datasets they want to use in building AI models, publish datasets, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges..

  • Computer Vision Applications

    Facial recognition.Self-driving cars.Robotic automation.Medical anomaly detection.Sports performance analysis.Manufacturing fault detection.Agricultural monitoring.Plant species classification.
  • A dataset is a collection of samples (in this case, images or video) used to train and test machine learning models.
    Datasets usually contain examples that belong to a particular topic or domain.
    Open datasets are datasets available for anyone to download and use freely.
Download Open Datasets on 1000s of Projects + Share Projects on One Platform. Explore Popular Topics Like Government, Sports, Medicine, Fintech, Food, More.

Experimental video conferencing method by Google

Project Starline is an experimental video communication method currently in development by Google that allows the user to see a 3D model of the person they are communicating with.
Google announced the product at its 2021 I/O developer conference, saying that it will allow users to talk naturally, gesture and make eye contact by utilizing machine learning, spatial audio, computer vision and real-time compression to create the 3D effect without the user wearing typical virtual reality goggles.
The goal is to make the user feel as if they are in the same room with the other user.

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