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Embedded Systems and Deep Learning
United States
Приєднався 14 чер 2013
This video channel includes two parts:
(1) Embedded system programming. It includes tutorials for the book Embedded Systems with ARM Cortex-M Microcontrollers in Assembly Language and C (Forth Edition), Author: Yfieng Zhu, ISBN-13: 978-0982692677.
(2) Deep learning. It includes paper reviews and tutorials for modern deep-learning models.
(1) Embedded system programming. It includes tutorials for the book Embedded Systems with ARM Cortex-M Microcontrollers in Assembly Language and C (Forth Edition), Author: Yfieng Zhu, ISBN-13: 978-0982692677.
(2) Deep learning. It includes paper reviews and tutorials for modern deep-learning models.
Lecture 1. Why use two's complement?
More information on the book website: web.eece.maine.edu/~zhu/book
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Відео
Rethinking Metal Casting from an Additive Manufacturing Perspective
Переглядів 5619 місяців тому
Title: Rethinking Metal Casting from an Additive Manufacturing Perspective Speaker: Dr. Philip King, Assistant Professor, Mechanical Engineering, University of Maine Abstract: Metal casting is an old but important manufacturing technology. While traditional metal casting has existed for thousands of years, it remains a complex process under controlled conditions that suffers from variable casti...
Design and Manufacturing of New Functional Ceramic Composites
Переглядів 687Рік тому
Abstract: The route of devising polymer-derived ceramics (PDCs), which relies on heat treatment to convert preceramic polymers to ceramics, presents a flexible and energy-efficient approach to fabricate a broad spectrum of ceramics and in-situ ceramic-polymer composites with binary or multinary phases. Understanding the relationship among processing parameters, phase composition and material re...
Complex, Customizable, and Continual Learners for AI in Advanced Manufacturing by Dr. Nick Cheney
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Abstract: One of the hallmarks of advanced manufacturing is a shift from the homogenous designs and repetitive tasks of mass production to unique, customizable, and adaptable designs and manufacturing processes. Recent advances in machine learning hold great promise for various aspects of advancements to manufacturing. For example, generative models provide opportunities for design automation o...
Paper review: Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding
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Paper review: Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding
Paper review: Bayesian Deep Learning and a Probabilistic Perspective of Generalization
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Paper review: Bayesian Deep Learning and a Probabilistic Perspective of Generalization
Paper Review: DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation
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Paper Review: DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation
Paper Review: SAIL: Analyzing structural artifacts of logic locking using machine learning
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Paper Review: SAIL: Analyzing structural artifacts of logic locking using machine learning
Paper Review: Learning to Solve Hard Minimal Problems (Paper review, Zhongao Xu)
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Paper review of the paper "Learning to Solve Hard Minimal Problems" authored by Petr Hruby, Timothy Duff, Anton Leykin, Tomas Pajdla, arxiv.org/abs/2112.03424
Paper Review: Bayesian Uncertainty (Masoud Ataei)
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Paper Review: Bayesian Uncertainty (Masoud Ataei)
Paper Review: Swin Transformer (Saher Fatima)
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Paper Review: Swin Transformer (Saher Fatima)
Paper Review: Rebotics Reinforcement Learning (Niranjan Bhujel)
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Paper Review: Rebotics Reinforcement Learning (Niranjan Bhujel)
Paper Review: Informer (Harris Dorothy)
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Paper Review: Informer (Harris Dorothy)
Paper Review: Modeling Long- and Short-Term Temporal Patterns (Samuel Aremu)
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Paper Review: Modeling Long- and Short-Term Temporal Patterns (Samuel Aremu)
Paper Review: Openai zeroshot classifier (CLIP)
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Paper Review: Openai zeroshot classifier (CLIP)
Paper Review: Multimodal Approach to Zero-Shot Classification (Sarah Glatter)
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Paper Review: Multimodal Approach to Zero-Shot Classification (Sarah Glatter)
Paper Review: Vision transformers and adapters (Jason Halliday)
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Paper Review: Vision transformers and adapters (Jason Halliday)
Paper Review: Gigapixel image compression (Zafaryab Haider)
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Paper Review: Gigapixel image compression (Zafaryab Haider)
Paper Review: EASY: Ensemble Augmented-Shot Y-Shaped Learning (Jordan Miner)
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Paper Review: EASY: Ensemble Augmented-Shot Y-Shaped Learning (Jordan Miner)
Paper Review: Anomaly Detection (Joseph Patton)
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Paper Review: Anomaly Detection (Joseph Patton)
Paper Review: Temporal Fusion Forecasting (Christopher Ewanik)
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Paper Review: Temporal Fusion Forecasting (Christopher Ewanik)
Paper Review: Replicating Humanlike Gameplay in a Multi Agent Environment (Josh Hamilton)
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Paper Review: Replicating Humanlike Gameplay in a Multi Agent Environment (Josh Hamilton)
Paper Review: ViT Adapter (Devin Hoskins)
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Paper Review: ViT Adapter (Devin Hoskins)
Lecture 31. Preserving registers in a Subroutine
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Lecture 31. Preserving registers in a Subroutine
Lecture 30. Passing Arguments to a Subroutine
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Lecture 30. Passing Arguments to a Subroutine
Hall Kimberly Lopez Larry Jones Frank
thank you very much!
Precisely as always. Thanks
Thank you! very clear and helpfull!
Great explanaition. Thank you for your effort and great teaching skills. Best wishes.
This short video explains very smoothly and understandable💯😊
Vslsiosai
Very good explanation
Thank you Professor! The video is great!
try to talk with your original accent, the content can be improved
my god its blowing my mind!!
First time listening to Nick speak about his work, just started watching, great to see you are looking at Dr. Josh Bongard, and Dr. Michael Levin's work at Tufts University, when I first came across you I thought you were all aware of each other, cool
*Professor, are you going to be able to make tutorials on UART, I2C, and SPI? with lecture slides?*
Why the output of PB2 is also stored in the registor3 after exit from the systick_handler()
64 + 4 *n , could you clarify the formula in more details, please? Thanks a million.
*Dr.Zhu for President!!!!*
teşekkürler🙏
this video saved my 5 hour
is it correct that you said at 8:47 that ptr=ptr+2*sizeof(int)? or you meant *(ptr+2) is equal to ptr+2*sizeof(int) ?? because in your code the value of the ptr is not updated.
Best explanation, thank you 👍
Simple, easy and precise! Great explanation!! Thank you so much!!🙏❣
you ace every video. thank you. hope you will make a video about the peripheral communication.
Does the reload wait until ISR has completed or does it reload as soon as it reaches 0?
Many thanks for the reviews
Good video, i have an question though, if i understand correctly the tokenizer learns to tokenize each patch of image to an integer. since there is a very large possible combinations of pixel in each token, won't the size of the vocabulary of the tokenizer become extremely large?
So u are using little endian ?
I can finally do my engineering homework
Dr. Zhu, do you plan on uploading lectures from your Microcomputer Architecture and Applications course? Please consider doing so if possible- it would really help those of us that are trying to learn from your book.
Thank u!
Great explaination, thank you!
Very well explained sir. Thanks for the info!
Thank you robot for the clear explanation, using an almost dead, emotionless voice.
very well explained
LayerNorm does not reduce the channel dimension (12:30) , it is the Linear layer that does so.
Your channel is a hidden gem, a lot of your videos explain things in a way that are both clear and concise. Keep going!
Hi Professor, At 7:43 , you say - "In the Boot mode, processor can reprogram the Flash memory or Perform the device firmware upgrade". Please can you help me understand : 1) Why reprogramming the Flash memory is done ? 2) Please can you make video on "How device firmware upgradation is done by BootROM(boot memory). Can you please point me some resources to read. Thanks 🙏
Hi I think I can help you with the first question, the bootloader that exists in system memory is a set of instructions that can do multiple things like reading the received program from the UART interface and upload it to the flash memory (that how programing uC done)
Very good video
How are SP and PC set when the boot is from SRAM? SRAM will have some random values on reset
Wow! This is the clearest explanation of Pointers I have encountered. Thanks! 😊
sir for stm32f401re , the normal code HAL_GPIO_WritePin(GPIOA,GPIO_PIN_5,1); HAL_Delay(500); HAL_GPIO_WritePin(GPIOA,GPIO_PIN_5,0); HAL_Delay(500); pin pb3 = swo, pa14 = tck and pa13 = tms , what variable name should i give in the current logic analyser window
Thank you so much, very helpful to understand implementation, and apply the floating point unit of the microcontroller.
Thanks!
Where can I learn such command like GPIOB -> MODER &= ~(3UL<<4) that it actually do something rather than saying it clears bits or change bits, etc.. I already got knowledge about microprocessor and most logic operators so when you explain the 32 bits, i really got no problem with that. It just the code that I'm afraid of... Anyway, very brief and clear lecture. I hope I can learn more from this channel to fulfill my dedication in STM32
Great I was getting issues. It is solved now with ur video help. thanks
good explanation but volatile keyword is such a BS that its meaning is ambiguity itself. In this demo, we should assume that it's compiler bug! Why optimize out a memory access when a) systick handler accesses the memory area b) they are advertising their product is a compiler for embedded system development. The compiler should know!
Do not agree that Volatile is BS but my exact thought was that systick handler is already there in startup code, why compiler not aware about this?
great
great lecture
Can you explain AFIO
great video!! super helpful
its really helpful keep going