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前端微信小程序,后端Java还有硬件端

-demo icon -demo

一个小小的项目,主要是定位到当前城市然后展示当前城市的天气情况(温度、湿度等等)、还有未来3天的天气,包括通过输入城市名查找天气

-nodemcu- icon -nodemcu-

利用apollo服务器作为代理,android手机和ESP8266 NodeMCU作为客户端实现一个空气质量检测app。温湿度、MQ烟雾值以及PM2.5这些数据值都是通过硬件模块采集发布到服务器上去的。

3dus_project icon 3dus_project

Segmentation of ultrasound thyroid nodules using neural networks

acn icon acn

Redirection of ACNet repo.

agnet icon agnet

The code of "Attention Guided Network for Retinal Image Segmentation" in MICCAI 2019

ai-knowledge-graph icon ai-knowledge-graph

Build a complete AI domain Knowledge Graph or Wikipedia fo AI to Connect AI technologies and projects!

aptos2019 icon aptos2019

43th place (top2%) Solution for Kaggle APTOS 2019 Blindness Detection

arl icon arl

The pytorch implement for Attention Residual Learning for Skin Lesion Classification

attention-cnn icon attention-cnn

Source code for "On the Relationship between Self-Attention and Convolutional Layers"

attention-gated-networks icon attention-gated-networks

Use of Attention Gates in a Convolutional Neural Network / Medical Image Classification and Segmentation

augmentation_gan icon augmentation_gan

GAN-based Synthetic Medical Image Augmentation for increased CNN Performance in COVID-19 Classification

augmentor icon augmentor

Image augmentation library in Python for machine learning.

autoaugment icon autoaugment

Unofficial implementation of the ImageNet, CIFAR 10 and SVHN Augmentation Policies learned by AutoAugment using pillow

autodeeplab icon autodeeplab

Pytorch Implementation the paper Auto-DeepLab Hierarchical Neural Architecture Search for Semantic Image Segmentation

autodeeplab-1 icon autodeeplab-1

AutoDeeplab / auto-deeplab / AutoML for semantic segmentation, implemented in Pytorch

awesome-algorithm-books icon awesome-algorithm-books

📚 awesome algorithm books I've collected 【不定期更新】 搜集整理的算法书籍(经典算法、ML/DL算法、面试算法、比赛算法等)

balancecarbluno icon balancecarbluno

用于校创项目,android手机端,蓝牙数据传输部分代码

blindness-detection icon blindness-detection

The dataset I have worked on is a part of an online Kaggle competition- APTOS 2019 Blindness Detection. The goal of this competition is to detect blindness before it happens, organized by APTOS, data taken from Aravind Eye Hospitals here, in my home country India. In this synchronous Kernels-only competition, you’ll build a machine learning model to speed up disease detection. You’ll work with thousands of images collected in rural areas to help identify diabetic retinopathy automatically. If successful, you will not only help to prevent lifelong blindness, but these models may be used to detect other sorts of diseases in the future, like glaucoma and macular degeneration.This blog post is meant to provide a good starting point and insights for those who use PyTorch for training and fine-tuning your models.

blindness-detection-diabetic-retinopathy- icon blindness-detection-diabetic-retinopathy-

This is a 5 Class Image Classification Task based on a Kaggle dataset from Eye Images (Aravind Eye hospital) - APTOS 2019 Challenge. The goal is to predict the Blindness Stage (0-4) class from the Eye retina Image using Deep Learning Models (CNN). This Automated System would speed up Blindness detection on Patients

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