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machinelearninginaction

Source Code for the book: Machine Learning in Action published by Manning

map

mean Average Precision - This code evaluates the performance of your neural net for object recognition.

mask_rcnn

Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

mmdetection

OpenMMLab Detection Toolbox and Benchmark

note_save

patternrecognitionanddeeplearning-lab

2019春哈工大模式识别与深度学习实验

pinnpapers

Must-read Papers on Physics-Informed Neural Networks.

pinns

Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations

plsp

Algorithms to derive a land surface phenology product from PlanetScope imagery for AmeriFlux and NEON sites

pumpkin-book

《机器学习》（西瓜书）公式推导解析，在线阅读地址：https://datawhalechina.github.io/pumpkin-book

pydata-notebook

利用Python进行数据分析 第二版 (2017) 中文翻译笔记

python-vegindex

Python package to generate vegetation index timeseries from PhenoCam images.

python_for_data_analysis_2nd_chinese_version

《利用Python进行数据分析·第2版》

pytorch-cifar100

Practice on cifar100(ResNet, DenseNet, VGG, GoogleNet, InceptionV3, InceptionV4, Inception-ResNetv2, Xception, Resnet In Resnet, ResNext,ShuffleNet, ShuffleNetv2, MobileNet, MobileNetv2, SqueezeNet, NasNet, Residual Attention Network, SENet)

pytorch-mask-rcnn

pytorch-vgg-cifar10

This is the PyTorch implementation of VGG network trained on CIFAR10 dataset

pytorch-yolov4

Minimal PyTorch implementation of YOLOv4

qgis-earthengine-plugin

Integrates Google Earth Engine and QGIS using Python API

roadnet

RoadNet: A Multi-task Benchmark Dataset for Road Detection, TGRS.

roads

road extraction

roadtracer

rootdetector

Analysis tool for minirhizotron images

ruan-pheno

simple-faster-rcnn-pytorch

A simplified implemention of Faster R-CNN that replicate performance from origin paper

spatiotemporal_investigation_of_the_vegetation_phenology

Spatiotemporal investigation of the vegetation phenology based on the 3D urban morphology characterization

text_classification

all kinds of text classification models and more with deep learning

tianchi_-agricultural-forecast

依据广西81个县早稻、晚稻作物4年产量的相关历史数据，结合4年气象降雨、温度、光照、温差等气象数据，一方面探索广西各地区气象环境局部特征，构建未来气象预测系统，另一方面挖掘气象和水稻产量的关系，构建因地制宜精准产量预测模型。

train-yolov4-pytorch

YOLOV4 训练自己的数据集（VOC）

tropical_phenology_gee

Analysis of tropical phenology using GEE

voc2007_for_yolo_torch

prepare dataset for voc https://github.com/ultralytics/yolov3