Coder-Loser

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/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/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