- Видео 222
- Просмотров 4 418 561
Rich Radke
США
Добавлен 24 авг 2010
I'm a Professor in the ECSE (Electrical, Computer, and Systems Engineering) department at Rensselaer Polytechnic Institute (RPI), where my students and I research topics in computer vision, the study of algorithms for automatically understanding images. After many years of teaching image processing courses, I became particularly interested in the computer vision algorithms behind Hollywood visual effects (VFX), which are the topic of my first book and video series. Since then, I've recorded lectures for my courses on image processing, digital signal processing, and engineering probability. I hope you find them useful!
For more information, please visit my professional page, www.ecse.rpi.edu/~rjradke/research.htm.
For more information, please visit my professional page, www.ecse.rpi.edu/~rjradke/research.htm.
Computational Creativity Lecture 22: Generative models for X (vector graphics, layouts, animation)
Computational Creativity Lecture 22: Generative models for X (vector graphics, layouts, animation)
Rich Radke
Department of Electrical, Computer, and Systems Engineering
Rensselaer Polytechnic Institute
Rich Radke
Department of Electrical, Computer, and Systems Engineering
Rensselaer Polytechnic Institute
Просмотров: 309
Видео
Computational Creativity Lecture 21: Generative models for 3D
Просмотров 2917 месяцев назад
Computational Creativity Lecture 21: Generative models for 3D Rich Radke Department of Electrical, Computer, and Systems Engineering Rensselaer Polytechnic Institute
Computational Creativity Lecture 20: 3D representations and neural radiance fields (NeRFs)
Просмотров 2397 месяцев назад
Computational Creativity Lecture 20: 3D representations and neural radiance fields (NeRFs) Rich Radke Department of Electrical, Computer, and Systems Engineering Rensselaer Polytechnic Institute
Computational Creativity Lecture 19: Generative Models for Music
Просмотров 2067 месяцев назад
Computational Creativity Lecture 19: Generative Models for Music Rich Radke Department of Electrical, Computer, and Systems Engineering Rensselaer Polytechnic Institute (note: sorry the music is a bit soft in the video; hard to optimize for both recording and live classroom presentation.)
Computational Creativity Lecture 18: Diffusion Developments
Просмотров 2617 месяцев назад
Computational Creativity Lecture 18: Diffusion Developments Rich Radke Department of Electrical, Computer, and Systems Engineering Rensselaer Polytechnic Institute
Computational Creativity Lecture 16: CLIP and its applications
Просмотров 2167 месяцев назад
Computational Creativity Lecture 16: CLIP and its applications Rich Radke Department of Electrical, Computer, and Systems Engineering Rensselaer Polytechnic Institute
Computational Creativity Lecture 17: DALL-E 2 and Stable Diffusion
Просмотров 2217 месяцев назад
Computational Creativity Lecture 17: DALL-E 2 and Stable Diffusion Rich Radke Department of Electrical, Computer, and Systems Engineering Rensselaer Polytechnic Institute
Computational Creativity Lecture 15: Large language models and their implications
Просмотров 2248 месяцев назад
Computational Creativity Lecture 15: Large language models and their implications Rich Radke Department of Electrical, Computer, and Systems Engineering Rensselaer Polytechnic Institute
Computational Creativity Lecture 14: Attention and transformers
Просмотров 3388 месяцев назад
Computational Creativity Lecture 14: Attention and transformers Rich Radke Department of Electrical, Computer, and Systems Engineering Rensselaer Polytechnic Institute
Computational Creativity Lecture 13: Neural language models and word embeddings
Просмотров 2458 месяцев назад
Computational Creativity Lecture 13: Neural language models and word embeddings Rich Radke Department of Electrical, Computer, and Systems Engineering Rensselaer Polytechnic Institute
Computational Creativity Lecture 12: Normalizing flow models
Просмотров 2268 месяцев назад
Computational Creativity Lecture 12: Normalizing flow models Rich Radke Department of Electrical, Computer, and Systems Engineering Rensselaer Polytechnic Institute
Computational Creativity Lecture 11: Denoising diffusion models
Просмотров 4728 месяцев назад
Computational Creativity Lecture 11: Denoising diffusion models Rich Radke Department of Electrical, Computer, and Systems Engineering Rensselaer Polytechnic Institute
Computational Creativity Lecture 10: DeepDream and neural style transfer
Просмотров 2498 месяцев назад
Computational Creativity Lecture 10: DeepDream and neural style transfer Rich Radke Department of Electrical, Computer, and Systems Engineering Rensselaer Polytechnic Institute
Computational Creativity Lecture 9: Image-to-Image GANs and GAN artists
Просмотров 2539 месяцев назад
Computational Creativity Lecture 9: Image-to-Image GANs and GAN artists Rich Radke Department of Electrical, Computer, and Systems Engineering Rensselaer Polytechnic Institute
Computational Creativity Lecture 8: Advanced GANs
Просмотров 3159 месяцев назад
Computational Creativity Lecture 8: Advanced GANs
Computational Creativity Lecture 7: Generative Adversarial Networks (GANs)
Просмотров 3569 месяцев назад
Computational Creativity Lecture 7: Generative Adversarial Networks (GANs)
Computational Creativity Lecture 6: VQ-VAEs and image quality metrics
Просмотров 4699 месяцев назад
Computational Creativity Lecture 6: VQ-VAEs and image quality metrics
Computational Creativity Lecture 5: Variational autoencoders
Просмотров 4689 месяцев назад
Computational Creativity Lecture 5: Variational autoencoders
Computational Creativity Lecture 4: Deep Learning Crash Course
Просмотров 5069 месяцев назад
Computational Creativity Lecture 4: Deep Learning Crash Course
Computational Creativity Lecture 3: Probability and machine learning review
Просмотров 6019 месяцев назад
Computational Creativity Lecture 3: Probability and machine learning review
Computational Creativity Lecture 2: Algorithms for Making Art (~1960-2010)
Просмотров 8109 месяцев назад
Computational Creativity Lecture 2: Algorithms for Making Art (~1960-2010)
Computational Creativity Lecture 1: Introduction to Generative Models
Просмотров 2,5 тыс.9 месяцев назад
Computational Creativity Lecture 1: Introduction to Generative Models
Computer Vision for Visual Effects 2021
Просмотров 2 тыс.2 года назад
Computer Vision for Visual Effects 2021
Electrical, Computer, and Systems Engineering at Rensselaer
Просмотров 2,7 тыс.3 года назад
Electrical, Computer, and Systems Engineering at Rensselaer
PB45: The Joint Gaussian Random Variable
Просмотров 7 тыс.3 года назад
PB45: The Joint Gaussian Random Variable
danke <33
The explanation is fantastic, I was familiar with DSP before, but this one brought my knowledge to a new level. The explanation clearly includes the formulations and their visualization, making it crucial for us to learn the foundation. Thank you, sir!
this series explains the theory so much better than my profs thank you!
Best DSP course on RUclips forever 🎉 Can you share the book of dsp and notes that are used in vedios.
Great lecture!
This is epitome of effective teaching!
This is insanely well explained. I now remember why I loved maths at the university.
Ağzına sağlık Rich ağabey
you going to save my life omg
Hi, thanks for very helpful series. At 51:00, I'm not clear how the |C| * e^(rt) creates an "envelop". When r<0, it obviously creates the upper part of the "envelop", but where does the lower part of the "envelop" come from?
Think of a graph of exponential when r < 0. It decreases, so does cosine amplitude in this envelope. So it is not like e^rt will have both upper and lower parts of the envelope, but rather exponential nature will create them.
It's almost unbelievable how good these explanations are! Thank you so much!
At min 20 I think it is Acos(phi) not A sin(phi)
Hello. Thanks for your videos. But can I ask why do we need to know that signal is odd or even and etc. Does it have sm meaning for processing or future manipulation of signal?
That’s because FS and FT have even and odd part too
Thank you sir !
Very well taught, thanks Prof. Radke.
Perfect!
best DSP series on YT
I posted some critical comments on Lec 01 and it got deleted (presumably by the owner of the channel) after a few minutes 🤣. If you want your comments to be not deleted, sing paeans 🤣🤣. Even this comment will most likely get deleted!!
@@vvanamali6286 It is a free course. If you don't have anything nice to say, don't say it. It's not like you are paying the guy. So why should he listen to your whining?
@@hedgehog_fox It is silly to state that only "nice comments" should be posted. In the comment of mine that was deleted, I had pointed out things that were either misleading or incorrect. Examples: (i) x[a] when 'a' is not an integer is undefined and not zero. This point is glossed over when defining quantities like x[n/3], and (ii) while defining the derivative of u(t), it is being implied that delta(t) = infinity at t=0. This is wrong. Yes, the video is free. You seem to imply that misleading stuff can therefore be part of its content. Actually, if misleading stuff is posted, it should be called out so that those who are learning don't gulp it down unquestioningly. Without even knowing the contents of the deleted comment, you have been gratuitously labelled my response as "whining". Oh well.
¡Excelente trabajo!
Thanks for posting this series! Helpful as I approach video processing and compression.
Thank you! Great material to watch over the summer
I immediately hear the aliasing on the background