Models supported: ResNet, ResNetV2, SE-ResNet, ResNeXt, SE-ResNeXt [layers: 18, 34, 50, 101, 152] (1D and 2D versions with DEMO for Classification and Regression).
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Updated
Jan 27, 2022 - Jupyter Notebook
Models supported: ResNet, ResNetV2, SE-ResNet, ResNeXt, SE-ResNeXt [layers: 18, 34, 50, 101, 152] (1D and 2D versions with DEMO for Classification and Regression).
Models Supported: Inception [v1, v2, v3, v4], SE-Inception, Inception_ResNet [v1, v2], SE-Inception_ResNet (1D and 2D version with DEMO for Classification and Regression)
2D image convolution example in Python
Models Supported: VGG11, VGG13, VGG16, VGG16_v2, VGG19 (1D and 2D versions with DEMO for Classification and Regression).
A General Medical Image Segmentation Framework.(Multi-Modal, Mono-Modal, 2D, 3D)
Digital Image Processing with Matlab
2D Convolution apply in Frequency Domain
A collection of Jupyter notebooks containing various MNIST digit and fashion item classification implementations using fully-connected and convolutional neural networks (CNNs) built with TensorFlow and Keras. 2020.
Here is the Computer assignments material I designed for the Signals & Systems Winter 1400, instructed by Dr. Rabiei.
Noise2Noise is an AI denoiser trained with noisy images only. We implemented a ligther version which trains faster on smaller pictures without losing performance and an even simpler one where every low-level component was implemented from scratch, including a reimplementation of autograd.
Set of 2D & 1D CNN models to classify images of handwritten numbers from the MNIST dataset using Keras.
Speech Emotion Recognition using 1D and 2D Convolutional Neural Networks
NLP Project - Sentence Classification - Toxicity- Approx 20,000 comments - ranging from 2 to 30 words. Balanced Data Set. 1. Traditional, pre-2010 NLP and ML techniques used. 2. Dense Word Vectors - w2v & Glove, sentence vector created from averaged word vectors, ANN. 3. Glove combined with bi-LSTMs and 2D Convs.
This repository contains Convolutional Neural Networks implemented from scratch.
University project of the Parallel Computing course. There are two challenges that are solved using parallel computing techniques and two famous frameworks: OpenMP and CUDA.
A larger data science project that uses a 2D Convolutional Neural Network to determine the likelyhood of having covid-19 via CT images
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