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Practice Problem: Intel Scene Classification Challenge

About the Event

There has been a tremendous increase in the applications of computer vision. The applications of CV range from smart cameras and video surveillance to robotics, transportation and more.

Intel remains at the forefront to enable developers and data scientists build useful CV applications optimisedfor Intel processor architecture.

We encourage the participants to use the new OpenVINO™ toolkit by Intel. Short for Open Visual Inference & Neural Network Optimisation, the OpenVINO™ toolkit (formerly Intel® CV SDK) contains optimisedOpenCV and OpenVX libraries, deep learning code samples, and pre-trained models to enhance computer vision development. It’s validated on 100+ open source and custom models, and is available absolutely free. You can get started with the toolkit from the resources provided at thislink

Prize:

  • 1st: Rs. 35,000
  • 2nd: Rs. 25,000
  • 3rd: Rs. 15,000

Rules

  • One person cannot participate with more than one user accounts.
  • You are free to use any tool and machine you have rightful access to.
  • You are free to use solution checker as many times as you want.

FAQs

  • Can I share my approach/code?

    Absolutely. You are encouraged to share your approach and code file with the community. There is even a facility at the leaderboard to share the link to your code/solution description.

  • I am facing a technical issue with the platform/have a doubt regarding the problem statement. Where can I get support?

    Post your query on discussion forum at the thread for this problem, discussion threads are given at the bottom of this page. You could also join the AV slack channel by clicking on 'Join Slack Live Chat' button and ask your query at channel: practice_problems.

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Registration Details

3025

Total registered

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Number of teams

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Spaces You Can Join

Data Science

Over here, you can engage in discussions, ask questions, share insights, and converse about all things Data Science, from regression models to LLMs!

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Generative AI

Over here, you can engage in discussions, ask questions, share insights, and converse about all things Data Science, from regression models to LLMs!

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Data Engineering

Over here, you can engage in discussions, ask questions, share insights, and converse about all things Data Science, from regression models to LLMs!

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Frequently Asked Questions

Find the answers for the most frequently asked questions

Participants benefit from one-on-one feedback, publication on a respected platform, recognition from a global audience, and monetary rewards for each published article. Additionally, the top articles receive special rewards.

Each article must be original, and pass plagiarism and not AI generated content checks. You can submit multiple articles as long as each is distinct. Proper citation of all references and image sources is mandatory.

There are no specific requirements to register for the hackathon, although it is recommended to have some basic knowledge of the relevant topics, such as Data Science, Machine Learning, or Deep Learning, along with proficiency in a coding language, preferably Python.

In the Blogathon, an article typically explores a specific topic or idea within Data Science or Generative AI and is required to be at least 1000 words long. A guide, on the other hand, is a more comprehensive resource, covering all aspects of a particular subject in data science, and must be at least 2500 words long. Guides aim to serve as a one-stop resource, providing detailed insights and practical applications, whereas articles might focus on narrower or more specific topics.

Depending on the type of competition, you can participate individually or in a team.

Multiple submissions of the same article are prohibited and could lead to disqualification. Articles failing to meet the required length, originality, or citation standards will be rejected.

AVCC is a community for authors who have had three or more articles published in the Blogathons. Members benefit from monetary rewards for each published article and get the opportunity to showcase their work to a larger audience.

You can access the problem statement under the "Problem Statement" tab once the Hackathon is live.

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