✅ Free course with problems:
► Object Detection with problems: https://stepik.org/a/224806
✅ Courses with problems:
► Pytorch with problems: https://clck.ru/3M9zft
► Pandas with problems: https://clck.ru/3M9zf4
► Numpy with problems: https://clck.ru/3M9zdf
✅ My Telegram channel: https://t.me/dubinin_ser
✅ Telegram groups:
► Pytorch: https://t.me/PyTorch_for_you
► Pandas: https://t.me/pandas_for_you
► Numpy: https://t.me/numpy_for_you
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Greetings, friends! If you're interested in computer vision and want to learn how to create your own models for object detection tasks, you've come to the right place!
In this video series, we'll explore the basics of object detection and explore various architectures.
Don't waste any time and join us on this exciting journey into the world of computer vision!
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In this video, we'll refresh our previous knowledge of convolutions and convolutional networks. We'll also explore what a receptive field is. We'll explore the differences between 5x5 and 3x3 convolutions. We'll see how stride affects the receptive field. And we'll take the first steps in understanding how object detection works.
Timecodes:
00:00 - Introduction.
00:29 - Brief review of convolutions.
01:15 - Receptive field.
02:28 - Comparison of 5x5 and 3x3 convolutions.
04:18 - Stride - a way to increase the receptive field.
05:19 - First steps to understanding detection.
Tags: #pytorch #AI #objectdetection #yolo