Introduction to Object Detection in Deep Learning

In this first video of this series in object detection we try to understand what object detection is and how it works. We also look at an overview of model architectures in object detection such as a sliding windows approach, regional based family of models (r-CNN) and lastly a quick overview of Yolo which we will go into more in depth (and code from scratch) in a future video!

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[patloeber]

Great! Looking forward to the YOLO implementation from scratch :)

[rushirajparmar]

This is a really great initiative!! Thanks man! I hope you cover segmentation algorithms and their implementations in PyTorch as well! That would be a complete series!

[林裕锋]

I'm glad I came across your video when I was confused about target detection😀

[shelby]

Great job. Cleary explanation. Motivated me to done all chapters

[asiskumarroy]

Great work brother, , was eagerly waiting for this.i have been following ur videos for quite a long time an it has helped me in my journey of learning the amazing Pytorch framework and implementing deep neural network models from scratch.I requested you by commenting in one of your videos to come up with the object detection series and at present I am overwhelmed to see this playlist.Cant wait to get my hands dirty in implementing YOLO from scratch.kudos to u brother.

[thetensordude]

Brother thanks for these computer vision videos! Love from India

[zukofire]

Thanks for this! It helps a lot (I'm doing an internship in computer vision!)

[sobuzvisual]

Hope for another great series. Thanks for sharing.

[jackiemai]

Thanks bro! i love your video! That can help me understand about the object detection more easily! I am a beginner on deep learning from China ~ .Finally i believe we can be the good friends

[tobkin]

Awesome explainer thanks for making this content :) Didn't know how these classifiers worked and this video gave me a useful intuition

[vatsalkhetan]

You are doing such an incredible join man

[jakobhalskov]

Lovely introduction: informative and pleasant to listen to :) Will dig deep into your channel now!

[tawheedrony]

Hey! Back again in your channel skipping tensorflow tutorials :3 However I would request you to push the object detection tutorials with explaining some SOTA architectures. If you please!

[CommitSNIPS]

Great video, easy to follow and well structured graphics for visual learning

[DanielPietsch-or]

Hey, really enjoyed this video. Have you heared of FCOS object detector? Maybe you can consider to showcase this one in your next paper review? Best regards

[Mesenqe]

I was waiting for this series, hope to see more videos.

[algeralgerie]

Thanks for the video. Have yoou come any service or application for convolutional neural networks in remote sensing applications ?

[frankrobert]

Great series. Look forward to your more series.

[wolfisraging]

Yo, couldn't wait to see upcoming videos, I'm sure you'll kill it.

[_adi_]

Love this! Would you be covering other architectures in addition to Yolo? I've been trying to understand this stuff recently, but I can't picture what a single training cycle flow looks like for even relatively simpler architectures like overfeat. More than explaining the individual concepts, I am DYING to see how the pieces fit together to make just a single training cycle. I just can't seem to find a resource that does this, to help me break into the world of object detection. I hope you will turn out to be that resource I've been searching for. (sorry for the rant :))