Popular GitHub Repositories for Tensoflow

Tensoflow implementation of InsightFace (ArcFace: Additive Angular Margin Loss for Deep Face Recognition).

Official implementation of DoubleU-Net for Semantic Image Segmentation in TensorFlow & Pytorch (Nominated for Best Paper Award (IEEE CBMS))

ALBERT model Pretraining and Fine Tuning using TF2.0

The project surveys 16+ Natural Language Processing (NLP) research papers that propose novel Deep Neural Network Models for Text Classification, based on Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN). It also implements each of the models using Tensorflow and Keras.

TensorFlow Guide

Many market analysts believe that predicting market’s stocks fluctuations is nearly impossible to achieve due to the number of variables involved, especially since many of these variables are based on irrational factors such as human sentiment. However, I developed a model that uses a combination of sentiment analysis, clustering and feed-forward neural network in order to predict the market trends.

Deep learning project focused on dark matter searches

To predict a chinese name to be male or female

This repository contains a notebook for object detection with the help of fine tuning of a (TF2 friendly) RetinaNet architecture on very few examples of a novel class after initializing from a pre-trained COCO checkpoint. Training runs in eager mode.

Deep Learning models for GDP growth rate forecasting.

An all-in-one Python script for real-time audio and video processing with deep learning models. Simultaneously handling live video and audio streams, it accomplishes action recognition, object detection, and audio classification. Additionally, it seamlessly integrates Twilio for notifications and utilizes Azure for efficient data management.

Apply TensorFlow CNN to recognize handwritten Japanese characters (Furigana), and transfer to android to receive on-device input and recognize with TensorFlow Lite.

Computer Vision Project using Tensorflow to classify different diseases that appears on the plants' leaves into five categories; Healthy, Powdery, Rust, Slug and Spot with a web app to be used easily.

Computer Vision Project using Tensorflow to classify different diseases that appears on the plants' leaves into five categories; Healthy, Powdery, Rust, Slug and Spot with a web app to be used easily.