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    <h2>Information </h2>
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      <h5>Instructor: Professor R. Venkatesh Babu and Professor Anirban Chakraborty</h5>
      <!-- <h5>Organizational meeting: 9th August, 4:45PM at CDS 202.</h5> -->
      <h5>Classroom Venue: Room 202, CDS</h5>
      <h5>Class Timings: Monday and Wednesday, 12PM to 1:15PM.</h5>
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      <!-- <h5> Course Form: <a href= 'https://docs.google.com/forms/d/1NrG4Yb4hbQ_32aRw9b3x2Zekfnbc8Pg4S1J15kQD5NM/viewform?ts=5a5465a6&edit_requested=true' target='blank'> Link to Google Form</a></h5> -->
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      <h2>Brief description of the course</h2>

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<p>The goal of machine vision is to develop methods that enable a machine to “understand” or analyze images and videos. This course will address the research issues towards developing algorithms that can perform high-level visual recognition tasks on real-world images and videos. This course will review and discuss current approaches to high-level visual recognition problems, such as background modeling, object recognition and categorization, tracking, scene understanding, human motion understanding, etc. This course is intended for graduate level students.
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    <h2>Prerequisites</h2>
    <p>Primary crucial prerequisites : Image Processing
    </p><p>Secondary Prerequisites(familiarity preffered): Statistics and Linear Algebra.
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    <h2>Course Outcomes</h2>
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<li>Thoroughly Understanding the fundamentals of Video analytics.</li>
<li>Gaining Knowlegde about State-of the art models and Other Important Works in recent years.</li>
<li>Learning the skills to implement computer vision Systems(Use of Multiple packages etc.)</li>
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