Revisions and implementations of modern Convolutional Neural Networks architectures in TensorFlow and Keras
-
Updated
Oct 5, 2022 - Jupyter Notebook
Revisions and implementations of modern Convolutional Neural Networks architectures in TensorFlow and Keras
Generative deep learning: DeepDream
A collection of some easy Neural Network based Python projects
Estimating galaxy gas mass fractions using SDSS imaging
Official code for CVPR2024 “VideoMAC: Video Masked Autoencoders Meet ConvNets”
PyTorch 1.x version's Tutorials using Google Colab: Overview, Regression, ConvNets, RNNs, GANs tutorials, etc.
Neural style art transfer made using a VGG-16 convolutional neural network using Keras and TensorFlow.
Predicting Yaw and Pitch of a moving vehicle (comma ai) including more stuff that can help make your car drive itself.
Colorization of Image with Generative Adversarial Network (Pix2Pix).
Car Localization with Semantic Segmentation, using UNet. Dice Score: 0.89, Pixel to Pixel Accuracy: 99.07%.
Random Anime Face Generation with Generative Adversarial Networks. DCGAN and WGAN-GP are used.
Convolutional Neural Network to Classify Dogs and Cat. I built a ImageClassifier which classifies and tells you whether its a Dog image or a Cat image. I built a convolutional network which consists of Three Convolution layer and Three MaxPooling layer. Each Convolutional layer has filters, kernel size. Maxpooling layer has stride and pooling si…
These notes and resources are compiled from the crash course Prompt Engineering for Vision Models offered by DeepLearning.AI.
Visualization and adversarial examples with a DIY (numpy only) ConvNet.
Techniques for interpreting ConvNets
This is a Computer Vision Free Course from @Kaggle.
Add a description, image, and links to the convnets topic page so that developers can more easily learn about it.
To associate your repository with the convnets topic, visit your repo's landing page and select "manage topics."