Edward Peng's repositories
demo-for-aliyun-plant-api
阿里云市场智能植物识别（含花卉与杂草）API的调用示例代码（https://market.aliyun.com/products/57124001/cmapi018620.html#sku=yuncode1262000000）
2019-iflytek-competition-Alzheimer-s-disease-prediction
2019科大讯飞 阿尔茨海默综合症预测挑战赛baseline
2019-iflytek-competition-app-classification-labeling
2019大数据应用分类标注挑战赛 baseline
2019-iflytek-competition-app-classification-labeling-top8
2019科大讯飞开发者大赛——大数据应用分类标注挑战赛top8_solution
AD8232_Heart_Rate_Monitor
AD8232 Heart Rate Monitor
Advertising-algorithm-competition
2018 腾讯广告算法大赛/IJCAI 阿里妈妈搜索广告转化预测竞赛/讯飞广告营销算法/OGeek
Agricultural-Disease-Classification
AIchallenger2018 Agricultural-Disease 农作物病害检测
AgriculturalDiseaseClassification
Some time ago, I participated in a competition. Although the result was not very good, I learned a lot.
apkutils2
A library that gets infos from APK. Add some patch for https://github.com/mikusjelly/apkutils
ATB-Datathon
A plant disease image detection model created for the 2019 ATB Datathon Precision Agriculture Challenge
ccf_sales_volume
CCF大数据与计算智能大赛-乘用车细分市场销量预测
data_integration_celery
通过celery定期执行更相关任务，将万得wind，同花顺ifind，东方财富choice、Tushrae、JQDataSDK、pytdx、CMC等数据终端的数据进行整合，清洗，一致化，供其他系统数据分析使用
Deep-Learning-Image-Recognition
Can a machine identify a bee as a honey bee or a bumble bee? These bees have different behaviors and appearances, but given the variety of backgrounds, positions, and image resolutions, it can be a challenge for machines to tell them apart. Being able to identify bee species from images is a task that ultimately would allow researchers to more quickly and effectively collect field data. Pollinating bees have critical roles in both ecology and agriculture, and diseases like colony collapse disorder threaten these species. Identifying different species of bees in the wild means that we can better understand the prevalence and growth of these important insects.
digipathos-plant-pathology-dataset
Brazilian Agricultural Research Corporation (EMBRAPA) fully annotated dataset for plant diseases. Plug and play installation over PiP.
face-detection-induction-course
Basics of face detection, share detailed steps and complete code in the learning process.
face-detection-pytorch
Face detection algorithms in PyTorch.
iFLYTEK-_ad
科大讯飞广告欺诈大赛
iotBasedCropDiseaseDetection
In this project, an architecture is proposed which focuses on IOT and agriculture automation using the sensors and traditional crop disease detection methods. The architectural framework is general for variety of crops and their disease. To demonstrate working of this architecture the mango crop and its diseases is been chosen.
machine_learning
抽象来讲，机器学习问题是把数据转换成信息再提炼到知识的过程，特征是“数据-->信息”的过程，决定了结果的上限，而分类器是“信息-->知识”的过程，则是去逼近这个上限
Mobile-based-advisory-for-identification-and-management-of-insect-pest-in-agricultural-crops
Insect Pest take a heavy toll on agricultural crops causing severe loss to the farming community. Crop protection is one of the major components of crop management process. Crops are damaged by attack of disease, insect, nematodes and weeds. Managing them in the field and saving the crop from their attack is a major challenge for the farming community. Our crops are under threat from the day they are seeded til they are harvested causing significant damage to the crop affecting adversely to the farmer's economy. Many factors influence disease development and growth of insect that includes genetics of variety, plant growth stage, weather, soil etc. Most of these information on insects, disease etc has been identified and documented by the Scientists and available in various literatures. This documentation will have a better significance if they are reached out to the farming community whenever they need it. Developing a web or mobile app having a complete knowledge base of insect pest carrying its detail in the background will be of great help. It will help in identifying the insect pest in the farmers field based on the damaged symptom or 3 by the image of the insects. On identifying the insect pest the system may provide the management.
mouth-open
Detecting when a human's mouth is open
Plant-Disease-Detection
Plant Disease Detection is one of the mind-boggling issues when we talk about using Technology in Agriculture. Although researches have been done to detect whether a plant is healthy or diseased using Deep Learning and with the help of Neural Network, new techniques are still being discovered. For Fewer Data Classical Machine Learning Models are said to outstand given the data is pre-processed well. On the same theory here is my approach for Detecting whether a plant leaf is healthy or unhealthy by utilizing the classical Machine Learning Models, Pre-processing the Image Data. The data was fed to 7 Machine Learning Models with 10 fold cross-validation out of which Random Forest Classifier outperformed all the other models giving an accuracy of 97% on the test set.
Plant-Leaf-Disease-Detection-using-SVM
Single model which will be capable for detection of disease in various types of farming practices like floriculture, arboriculture, agriculture, cultivation, horticulture, etc.
stock-1
同花顺
stock-knowledge-graph
利用网络上公开的数据构建一个小型的证券知识图谱/知识库
Thesis-on-rice-leaf-disease-detection-using-convolutional-neural-network
Rice is the staple food of about 180 million people of Bangladesh. About 90% Bangladeshi eats rice as their daily food. It provides nearly 48% of rural employment and supplies about two-third of total calorie. Rice contributes one-sixth of the national income and one-half of the agricultural GDP in Bangladesh. Almost all of the 13 million farm families of the country cultivate rice. Rice is grown on about 10.5 million hectares which has remained over the past three decades. So, rice plays a vital role in the livelihood of the people of Bangladesh. But it is unfortunate that all the cultivated varieties of rice suffer from several diseases over its entire growth period. Diseases can affect both productivity and crop quality as well. Out of 31 rice diseases, 10 are considered as major diseases Among the diseases, bacterial leaf blight, brownspot, blast, tungro and sheath blight cause substantial loss to rice both in quality and quantity in the present ecosystem in Bangladesh. The detection of diseases is a quite hard task for farmers and experts with naked eyes. In modern agricultural practices, it is very important to manage diseases using highly efficient methods with minimum damage to the environment. So, we opt to develop an efficient CNN model for rice leaf diseases to provide the farmers an effective system to identify symptoms of various diseases by using captured images.
TongHuaShun-Spider
一个同花顺财经新闻的爬虫。
tonghuashun_crawler
同花顺智能选股的信息爬虫
weixin_crawler
高效微信公众号历史文章和阅读数据爬虫powered by scrapy