Pinned Repositories
AI-ForestWatch
AI-Practice-Tensorflow-Notes
人工智能实践:Tensorflow笔记
autoup
洛阳理工学院健康汇报
Crop-Yield-Prediction-Using-CNN-LSTM-
Crop yield prediction on remote sensing data using CNN
ENSO-ASC
ENSO-ASC 1.0.0: ENSO deep learning forecast model with a multivariate air-sea coupler
flow-forecast
Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).
LT-GEE_LandTrendr
Google Earth Engine implementation of the LandTrendr spectral-temporal segmentation algorithm. For documentation see:
mall
mall项目是一套电商系统,包括前台商城系统及后台管理系统,基于SpringBoot+MyBatis实现,采用Docker容器化部署。 前台商城系统包含首页门户、商品推荐、商品搜索、商品展示、购物车、订单流程、会员中心、客户服务、帮助中心等模块。 后台管理系统包含商品管理、订单管理、会员管理、促销管理、运营管理、内容管理、统计报表、财务管理、权限管理、设置等模块。
Multiple_years_yield_prediction
Multiple years' yield prediction based on soil, weather and UAV image data.
Multivariate_Timeseries_Forecasting
This repository provides a variety of deep learning-based approaches to multivariate time series prediction.
Coder-Loser's Repositories
Coder-Loser/AI-ForestWatch
Coder-Loser/AI-Practice-Tensorflow-Notes
人工智能实践:Tensorflow笔记
Coder-Loser/autoup
洛阳理工学院健康汇报
Coder-Loser/Crop-Yield-Prediction-Using-CNN-LSTM-
Crop yield prediction on remote sensing data using CNN
Coder-Loser/ENSO-ASC
ENSO-ASC 1.0.0: ENSO deep learning forecast model with a multivariate air-sea coupler
Coder-Loser/flow-forecast
Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).
Coder-Loser/LT-GEE_LandTrendr
Google Earth Engine implementation of the LandTrendr spectral-temporal segmentation algorithm. For documentation see:
Coder-Loser/mall
mall项目是一套电商系统,包括前台商城系统及后台管理系统,基于SpringBoot+MyBatis实现,采用Docker容器化部署。 前台商城系统包含首页门户、商品推荐、商品搜索、商品展示、购物车、订单流程、会员中心、客户服务、帮助中心等模块。 后台管理系统包含商品管理、订单管理、会员管理、促销管理、运营管理、内容管理、统计报表、财务管理、权限管理、设置等模块。
Coder-Loser/Multiple_years_yield_prediction
Multiple years' yield prediction based on soil, weather and UAV image data.
Coder-Loser/Multivariate_Timeseries_Forecasting
This repository provides a variety of deep learning-based approaches to multivariate time series prediction.
Coder-Loser/open-meteo
Free Weather Forecast API for non-commercial use
Coder-Loser/SuperMarket
设计精良的网上商城系统,包括前端、后端、数据库、负载均衡、数据库缓存、分库分表、读写分离、全文检索、消息队列等,使用SpringCloud框架,基于Java开发。该项目可部署到服务器上,不断完善中……
Coder-Loser/taotao
IDEA版本淘淘商城
Coder-Loser/timehetnet
Learning complex time series forecasting models usually requires a large amount of data, as each model is trained from scratch for each task/data set. Leveraging learning experience with similar datasets is a well-established technique for classification problems called few-shot classification. However, existing approaches cannot be applied to time-series forecasting because i) multivariate time-series datasets have different channels and ii) forecasting is principally different from classification. In this paper we formalize the problem of few-shot forecasting of time-series with heterogeneous channels for the first time. Extending recent work on heterogeneous attributes in vector data, we develop a model composed of permutation-invariant deep set-blocks which incorporate a temporal embedding. We assemble the first meta-dataset of 40 multivariate time-series datasets and show through experiments that our model provides a good generalization, outperforming baselines carried over from simpler scenarios that either fail to learn across tasks or miss temporal information.
Coder-Loser/vue-manage-system
基于Vue3 + Element Plus 的后台管理系统解决方案