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Language of Instruction
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English
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Level of Course Unit
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Master's Degree
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Department / Program
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ELECTRICAL AND COMPUTER ENGINEERING
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Type of Program
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Formal Education
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Type of Course Unit
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Elective
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Course Delivery Method
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Face To Face
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Objectives of the Course
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Helping students in understanding of foundations of image processing techniques.
Providing a broader view of common deep learning and CV problems.
Discussing recent advancements in the field of Deep Learning based Computer Vision.
Showing the implementation approaches of the DIP methods with examples.
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Course Content
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Since its introduction into the field of AI, Deep Learning (DL) became an inseparable part of Computer Vision (CV). This course will introduce fundamentals of neural networks, convolutional neural networks, apart from CNNs various other DL structures such as Unet, LSTM, Transformers etc. , their applications to CV problems, general research problems of CV and their solutions using DL, get familiar with cutting edge research in CV field. It will also provide information about python implementation of those methods, fine tunings, tips and tricks.
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Course Methods and Techniques
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Prerequisites and co-requisities
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None
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Course Coordinator
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None
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Name of Lecturers
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None
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Assistants
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None
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Work Placement(s)
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No
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Recommended or Required Reading
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