Pinned Repositories
2019-computefest
2020-ComputeFest
3D-convolutional-speaker-recognition
:speaker: Deep Learning & 3D Convolutional Neural Networks for Speaker Verification
acoustic-embeddings
Acoustic embeddings for speech recognition using VAEs
Advanced-Data-Science-with-IBM-Courses
Applied-DS-Capstone---IBM
Week 1 - Introduction to Capstone Project Introduction to Capstone Project Location Data Providers Signing-up for a Watson Studio Account Peer-review Assignment: Capstone Project Notebook Week 2 - Foursquare API Introduction to Foursquare Getting Foursquare API Credentials Using Foursquare API Lab: Foursquare API Quiz: Foursquare API Week 3 - Neighborhood Segmentation and Clustering Clustering Lab: Clustering Lab: Segmenting and Clustering Neighborhoods in New York City Peer-review Assignment: Segmenting and Clustering Neighborhoods in Toronto Week 4 - Capstone Project Week 5 - Capstone Project (Cont'd)
Clustering-Based-on-ANN---SOFM-and-LVQ---MATLAB-code-example
In this project, two of the most famous NN-based clustering methods, SOM and LVQ, will be implemented. (Code Examples in MATLAB)
multi-output-learning-project
Convex optimization course _ Final project _ Article implementation
VesSeg_2019
Retinal diseases are already the most common cause of childhood blindness worldwide. Accordingly, it would be extensively beneficial to populations and health-related communities if we can automate the procedure of diagnosis thoroughly or at least partially by exploiting capabilities of computer-aided diagnosis (CAD). This paper proposes two segmentation methods, a supervised method and an unsupervised one, which shall expertly tackle the problem of vessel segmentation in retinal fundus images. Dataset used in this research is the so-called DRIVE dataset which is public and has been established to enable comparative studies on segmentation of blood vessels, hence containing 2 groups that each group constitutes of 20 colour images for the purpose of train and test. Our supervised method has achieved a higher accuracy of 94.47% by exploiting support-vector-machine technique (SVM) as its intellect, and our unsupervised method has achieved an ample accuracy of 94.28%, with a response time of 1.65 second providing operators and/or systems with fast and reliable results.
alidastgheib's Repositories
alidastgheib/alidastgheib
I am an experienced developer of machine learning and deep learning algorithms.
alidastgheib/alidastgheib.github.io
My Personal Website
alidastgheib/Awesome-Super-Resolution
Collect super-resolution related papers, data, repositories
alidastgheib/AwesomeFakeNews
This repository contains recent research on fake news.
alidastgheib/COVID-19
Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE
alidastgheib/datasets
A collection of datasets of ML problem solving
alidastgheib/EEGAN
Edge Enhanced GAN For Remote Sensing Image Super-Resolution
alidastgheib/EESRGAN
Small-Object Detection in Remote Sensing (satellite) Images with End-to-End Edge-Enhanced GAN and Object Detector Network
alidastgheib/fashion-mnist
A MNIST-like fashion product database. Benchmark :point_down:
alidastgheib/image-super-resolution
🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.
alidastgheib/image-super-resolution-1
📷 A simple convolutional neural network for single image super-resolution
alidastgheib/Image-Super-Resolution-2
Implementation of Super Resolution CNN in Keras.
alidastgheib/imagecodecs
Image transformation, compression, and decompression codecs. Forked from https://pypi.org/project/imagecodecs
alidastgheib/imdb-corpus-for-MT
alidastgheib/multilingual-bert-text-classification
text classification using mbert
alidastgheib/nlp-notebooks
A collection of notebooks for Natural Language Processing from NLP Town
alidastgheib/open-data-registry
A registry of publicly available datasets on AWS
alidastgheib/Practical-Machine-Learning-__-project
Prediction Assignment for “Practical Machine Learning Course” at Coursera. By: Mohammad Ali Dastgheib _ jdastgheib@ gmail.com
alidastgheib/precourse
A repo for the pre-course work at home exercises
alidastgheib/srgan
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
alidastgheib/super-resolution-1
Tensorflow 2.x based implementation of EDSR, WDSR and SRGAN for single image super-resolution
alidastgheib/thundersvm
ThunderSVM: A Fast SVM Library on GPUs and CPUs
alidastgheib/tifffile
Read and write TIFF files. Forked from https://pypi.org/project/tifffile
alidastgheib/TinyGPSPlus
A new, customizable Arduino NMEA parsing library
alidastgheib/tokenizers
💥 Fast State-of-the-Art Tokenizers optimized for Research and Production
alidastgheib/transformers
🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.
alidastgheib/tweeteval
Repository for TweetEval
alidastgheib/twitter-sentiment-analysis-tutorial-201107
Code to reproduce the simple sentiment analysis from my presentation
alidastgheib/xlm-t
Repository for XLM-T, a framework for evaluating multilingual language models on Twitter data
alidastgheib/xview-yolov3
xView 2018 Object Detection Challenge: YOLOv3 Training and Inference.