implementation of neural network from scratch only using numpy (Conv, Fc, Maxpool, optimizers and activation functions)
-
Updated
Oct 9, 2022 - Python
implementation of neural network from scratch only using numpy (Conv, Fc, Maxpool, optimizers and activation functions)
An algorithm that facilitates communication between a speech-impaired person and someone who doesn't understand sign language using convolution neural networks
This repository consists of models of CNN for classifying different types of charts. Moreover, it also includes script of fine-tuned VGG16 for this task. On top of that CradCAM implementation of fine-tuned VGG16.
This repository provides a smooth max pooling implementation using the LogSumExp (LSE) function. Unlike traditional max pooling, which can result in sparse gradients, our approach approximates the maximum operation to ensure more effective gradient distribution.
Python implementation of the neural networks without using any libraries from scratch, for prediction using the pre-trained weights
A LeNet implementation, just for fun
Image Recognition using CNN
How positive is an IMDB movie review ?
Convolutional neural network implementation using NumPy
C1 under Tensorflow developer professional certificate (Coursera).
Add a description, image, and links to the maxpooling topic page so that developers can more easily learn about it.
To associate your repository with the maxpooling topic, visit your repo's landing page and select "manage topics."