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In this video, we take a look at depthwise separable convolutions. What is it? How does it work? Why do it? Code included!

Let's visualize what a convolution neural network actually learns, their feature maps and more! ABOUT ME ⭕ Subscribe: ...

In this video, we take a look 1x1 convolutions (point wise convolutions) and demonstrate what they are, why they are useful, ...

In this video, we take a look at Feature Pyramid Networks (FPN). What is it? How does it work? Why they are so useful in computer ...

In this video, we talk through why convolution networks are so effective with image processing. ABOUT ME ⭕ Subscribe: ...

Let's take a look at how convolution neural networks evolved diving into an early network called Neo-cognitron. Hopefully, we can ...

In this video, I try to explain the relationship between the transfer function and the impulse response of a linear passive system like ...

Analog and digital communications (Hinglish) I Course URL: https://onlinecourses.nptel.ac.in/noc26_ee03/preview Prof.

Subject : Mathematics Course Name : Advanced Partial Differential Equations – (Part I: Distributions and Sobolev Spaces) ...

Subject : Computer Science Course Name : Comprehensive View of Speech Processing Welcome to Swayam Prabha!

In this video I will discuss some of the more advanced features and best practices that you will find in more recent and modern ...

Lecture 08: Convolution Description: In linear time-invariant systems, breaking an input signal into individual time-shifted unit ...

In this video, we walk through the back propagation learning procedure in a convolution neural network, step by step. ABOUT ME ...

Lecture 05: Properties of Linear, Time-Invariant Systems Topics covered: Properties of linear, time-invariant systems, including the ...

Lecture 09: Fourier Transform Properties Topics covered: Linearity, symmetry, time shifting, differentiation and integration, time ...

Music and AI (PAT 498/598), University of Michigan, Winter 2025 Slides: ...

Lecture 04: Convolution Topics covered: Representation of signals in terms of impulses; Convolution sum representation for ...

Lecture 09: Frequency Response Description: The response of a system to sinusoidal input gives valuable information about its ...

In this video, we take a look at what the deep layers of a convolution neural network actually learn with some neat visuals.

Spatial convolution.