Deep Learning WS 20/21

Browse all posts in the Deep Learning WS 20/21 category.

13 to 18 of 66

27JAN 2021
Deep Learning WS 20/21
Watch now: Deep Learning: Segmentation and Object Detection – Part 3 (WS 20/21)
In this video, we start looking into object detection. We start with classical ideas, re-visit the concept of a fully convolutional neural network, and start developing a fast regional CNN detector which finally leads to Faster RCNN. Watch on:FAU TVFAU TV (no memes)YouTube Read the Transcript (Summer 2020) at:LMETowards Data Science
Read more about Watch now: Deep Learning: Segmentation and Object Detection – Part 3 (WS 20/21)
26JAN 2021
Deep Learning WS 20/21
Watch now: Deep Learning: Segmentation and Object Detection – Part 2 (WS 20/21)
In this video, we discuss ideas on how to improve on image segmentation. In particular skip connections as used in the U-Net have been applied very successfully here. Also, we, look into other advanced methods such as stacked hourglasses, convolutional pose machines, and conditional random fields in combination with deep learning. Watch on:FAU TVFAU TV […]
Read more about Watch now: Deep Learning: Segmentation and Object Detection – Part 2 (WS 20/21)
25JAN 2021
Deep Learning WS 20/21
Watch now: Deep Learning: Segmentation and Object Detection – Part 1 (WS 20/21)
In this video, we introduce the concepts of segmentation and object detection. For image segmentation, you use a CNN encoder in combination with a CNN decoder. We introduce several concepts on how to perform the upsampling in der decoder. Watch on:FAU TVFAU TV (no memes)YouTube Read the Transcript (Summer 2020) at:LMETowards Data Science
Read more about Watch now: Deep Learning: Segmentation and Object Detection – Part 1 (WS 20/21)
22JAN 2021
Deep Learning WS 20/21
Watch now: Deep Learning: Unsupervised Learning – Part 5 (WS 20/21)
In this last video on unsupervised learning, we introduce some more advanced GAN concepts to avoid mode collapse and strong intra-batch correlation using virtual batch normalization, unrolled GANs, and minibatch discrimination. Watch on:FAU TVFAU TV (no memes)YouTube Read the Transcript (Summer 2020) at:LMETowards Data Science
Read more about Watch now: Deep Learning: Unsupervised Learning – Part 5 (WS 20/21)
21JAN 2021
Deep Learning WS 20/21
Watch now: Deep Learning: Unsupervised Learning – Part 4 (WS 20/21)
In this video, we talk about conditional GANs and the CycleGAN. Watch on:FAU TVFAU TV (no memes)YouTube Read the Transcript (Summer 2020) at:LMETowards Data Science
Read more about Watch now: Deep Learning: Unsupervised Learning – Part 4 (WS 20/21)
20JAN 2021
Deep Learning WS 20/21
Watch now: Deep Learning: Unsupervised Learning – Part 3 (WS 20/21)
In this video, we talk about the basic ideas of Generative Adversarial Networks (GANs) and show some examples. Watch on:FAU TVFAU TV (no memes)YouTube Read the Transcript (Summer 2020) at:LMETowards Data Science
Read more about Watch now: Deep Learning: Unsupervised Learning – Part 3 (WS 20/21)