Pinned Repositories
CASED-Tensorflow
Simple Tensorflow implementation of "Curriculum Adaptive Sampling for Extreme Data Imbalance" with multi GPU using LUNA16 (MICCAI 2017) / LUNA16 Tutorial
interactive-tutorials
Interactive Tutorials
KSL
Lung-cancer-classification-using-LUNA16-dataset
This repository contains codes for preparing LUNA16 dataset and classifying it into nodule and not-nodule using CNN
lung-cancer-detection
Improve lung cancer detection using deep learning
PhpSpreadsheet
A pure PHP library for reading and writing spreadsheet files
stat212b
Topics Course on Deep Learning UC Berkeley
TensorFlow-Tutorials
TensorFlow Tutorials with YouTube Videos
Trash-GMCPP-dataset
Welcome to our repository! Inside, you'll find a rich collection of data that consists of 5 distinct classes of trash materials: metal, glass, cardboard, paper, and plastic. Along with the dataset, we have included xml and txt label files. These labels have been designed to make the dataset suitable for object detection.
Dotmim.Sync
A brand new database synchronization framework, multi platform, multi databases, developed on top of .Net Standard 2.0. https://dotmimsync.readthedocs.io/
HunarAA's Repositories
HunarAA/CASED-Tensorflow
Simple Tensorflow implementation of "Curriculum Adaptive Sampling for Extreme Data Imbalance" with multi GPU using LUNA16 (MICCAI 2017) / LUNA16 Tutorial
HunarAA/interactive-tutorials
Interactive Tutorials
HunarAA/KSL
HunarAA/Lung-cancer-classification-using-LUNA16-dataset
This repository contains codes for preparing LUNA16 dataset and classifying it into nodule and not-nodule using CNN
HunarAA/lung-cancer-detection
Improve lung cancer detection using deep learning
HunarAA/PhpSpreadsheet
A pure PHP library for reading and writing spreadsheet files
HunarAA/stat212b
Topics Course on Deep Learning UC Berkeley
HunarAA/TensorFlow-Tutorials
TensorFlow Tutorials with YouTube Videos
HunarAA/Trash-GMCPP-dataset
Welcome to our repository! Inside, you'll find a rich collection of data that consists of 5 distinct classes of trash materials: metal, glass, cardboard, paper, and plastic. Along with the dataset, we have included xml and txt label files. These labels have been designed to make the dataset suitable for object detection.