Yingyi Wu's Projects
Pytorch 3D U-Net Convolution Neural Network (CNN) designed for medical image segmentation
Aerial Image segmentation by PyTorch
Distributed Tensorflow, Keras and PyTorch on Apache Spark/Flink & Ray
Documentation and samples for ArcGIS API for Python
A curated list of awesome tools, tutorials, code, helpful projects, links, stuff about Earth Observation and Geospatial stuff!
An example project of how to use a U-Net for segmentation on medical images with PyTorch.
BigDL: Distributed Deep Learning Framework for Apache Spark
Step-by-step Deep Leaning Tutorials on Apache Spark using BigDL
BootstrapVue provides one of the most comprehensive implementations of Bootstrap v4 for Vue.js. With extensive and automated WAI-ARIA accessibility markup.
U-Net implementation in PyTorch for FLAIR abnormality segmentation in brain MRI
Winning building footprint detector implementations from the SpaceNet challenges.
YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )
第三方推送SDK
Satellite Imagery Feature Detection with SpaceNet dataset using deep UNet
Deep networks for Earth Observation
The Web framework for perfectionists with deadlines.
Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.
Multi-Class Semantic Segmentation on Dubai's Satellite Images.
TensorFlow examples
Hands-on Supervised Machine Learning with Python, Published by Packt
Official Kaggle API
A survey and reflection on the latest research breakthroughs in LLM-generated Text detection, including data, detectors, metrics, current issues and future directions.
Developing a well-documented repository for the Lung Nodule Detection task on the Luna16 dataset. This work is inspired by the ideas of the first-placed team at DSB2017, "grt123".
LUNA(LUng Nodule Analysis) 2016 Segmentation Pipeline
The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.
Training neural models with structured signals.
samples