2D Convolution in Computer Vision 📷

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Welcome to '2D Convolution in Computer Vision'! This computer vision tutorial aims to demystify one of the most crucial and foundational operations in the field of computer vision - the 2D convolution.

In the realm of computer vision, convolution is a mathematical operation that is used to process and transform images, making it a key component in image filtering and detection tasks. This operation revolves around the concept of a filter or kernel, typically a 3x3 or 5x5 matrix, which slides over the input image and manipulates it for further processing.

In this video, we will delve into an illustrative example where a 6x6 input is convolved with a 3x3 kernel. We'll break down the process step-by-step, making it easy for beginners to follow along and gain a solid understanding of how 2D convolution works.

Whether you're a beginner eager to learn the basics, an intermediate looking to solidify your knowledge, or an advanced learner interested in revisiting the fundamentals, this video will serve as a comprehensive guide to understanding 2D convolution in computer vision.

📚Please find an in-depth introductory video on this topic here: https://youtu.be/N15mjfAEPqw

⭐️ Time Stamps:⭐️
00:00-00:10: Introduction
00:10-02:30: Convolution Operation
02:30-03:11: Experimenting with Kernels
03:11-03:54: CNNs
03:54-04:49: Example
04:49-05:06: Outro

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