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Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models
pip install antialiased-cnns to improve stability and accuracy
🦖Pytorch implementation of popular Attention Mechanisms, Vision Transformers, MLP-Like models and CNNs.🔥🔥🔥
Revisions and implementations of modern Convolutional Neural Networks architectures in TensorFlow and Keras
Keras implementation of a ResNet-CAM model
Dilated CNNs for NER in TensorFlow
EEG Motor Imagery Tasks Classification (by Channels) via Convolutional Neural Networks (CNNs) based on TensorFlow
This repository contains my solutions to the assignments for Stanford's CS231n "Convolutional Neural Networks for Visual Recognition" (Spring 2020).
A quick view of high-performance convolution neural networks (CNNs) inference engines on mobile devices.
[NeurIPS '18] "Can We Gain More from Orthogonality Regularizations in Training Deep CNNs?" Official Implementation.
Code for the paper Language Identification Using Deep Convolutional Recurrent Neural Networks
Code repository of the paper "Wavelet Networks: Scale-Translation Equivariant Learning From Raw Time-Series, TMLR" https://arxiv.org/abs/2006.05259
Going deeper into Deep CNNs through visualization methods: Saliency maps, optimize a random input image and deep dreaming with Keras
several basic neural networks[mlp, autoencoder, CNNs, recurrentNN, recursiveNN] implements under several NN frameworks[ tensorflow, pytorch, theano, keras]
A Novel Approach to Video Super-Resolution using Frame Recurrence and Generative Adversarial Networks | Python3 | PyTorch | OpenCV2 | GANs | CNNs
Code repository for the paper "Attentive Group Equivariant Convolutional Neural Networks" published at ICML 2020. https://arxiv.org/abs/2002.03830
[CogSci'21] Study of human inductive biases in CNNs and Transformers.
The official PyTorch implementation for "Normalized Convolution Upsampling for Refined Optical Flow Estimation"
Presents comprehensive benchmarks of XLA-compatible pre-trained models in Keras.
Band-limited Training and Inference for Convolutional Neural Networks
Regression in Convolutional Neural Network applied to Plant Leaf Count
Glaucoma detection automation project. Trained a binary image classifier using CNNs and deployed as a streamlit web app. It takes eye (retinal scan) image as input and outputs whether the person is affected by glaucoma or not.
LeNet as a Feature Engineer-> LSTM for timeseries predicitions
Official Pytorch Code for "Exploring Overcomplete Representations for Single Image Deraining using CNNs" - IEEE Journal of STSP
An open source Verilog Based LeNet-1 Parallel CNNs Accelerator for FPGAs in Vivado 2017
ConvNeXt conversion code for PT to TF along with evaluation code on ImageNet-1k val.
This repo contains the source code of the project "FPGA implementation of BCIs using QCNNs" submitted to the Xilinx Open Hardware Design Competition 2021.
Code for our WACV 2021 paper "Exploiting the Redundancy in Convolutional Filters for Parameter Reduction"
Attention based Dual-Branch Complex Feature Fusion Network for Hyperspectral Image Classification
Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks..
Introduction to Deep Learning with TensorFlow by Udacity
In this repository you will find an end to end hands-on tutorial of an example of machine learning in production. The objective will be to create and deploy in the cloud a machine learning application able to recognize and classify different audio sounds.