mashiro210's Stars
mlichter2/concavity
Concave Hull boundary polygon for an array of points and concave and convex polygon vertex detection
cg-tuwien/ppsurf
Combining Patches and Point Convolutions for Detailed Surface Reconstruction
PlantSimulationLab/Helios
The Helios simulation system is a versatile modeling framework that handles tasks such as managing geometry and associated data structures through a C++ API. Plug-ins build off of the Helios core engine, and access the geometry and data via the Helios context. The sytem comes with a visualization plug-in that can produce stunning renderings of model geometry and data with relatively little effort.
mikeroyal/Photogrammetry-Guide
Photogrammetry Guide. Photogrammetry is widely used for Aerial surveying, Agriculture, Architecture, 3D Games, Robotics, Archaeology, Construction, Emergency management, and Medical.
CVHub520/X-AnyLabeling
Effortless data labeling with AI support from Segment Anything and other awesome models.
soskuthy/gamm_intro
ml-explore/mlx
MLX: An array framework for Apple silicon
rd4com/mojo-learning
📖 Learn some mojo !
cran/mppR
:exclamation: This is a read-only mirror of the CRAN R package repository. mppR — Multi-Parent Population QTL Analysis. Homepage: https://github.com/vincentgarin/mppR Report bugs for this package: https://github.com/vincentgarin/mppR/issues
OpenDroneMap/FIELDimageR
FIELDimageR: A R package to analyze orthomosaic images from agricultural field trials. This package is a compilation of functions to analyze pos-mosaicking images from research fields, and allows to: crop the image; remove soil effect; build vegetation indices; rotate the image; build the plot shapefile; extract information for each plot; and evaluate stand count, canopy percentage, and plant height.
filipematias23/FIELDimageR.Extra
Package with new tools to support FIELDimageR software on evaluating GIS images from agriculture field trials.
makora9143/gp-infer-net-pytorch
Re-implementation of Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019
nansencenter/DAPPER
Data Assimilation with Python: a Package for Experimental Research
satellite-image-deep-learning/techniques
Techniques for deep learning with satellite & aerial imagery
guoyongcs/DRN
Closed-loop Matters: Dual Regression Networks for Single Image Super-Resolution
deephdc/satsr
A project to perform super-resolution on multispectral images from any satellite
ZJiangsan/MSI_reconstruction_from_natRGB
kakkapriyesh/AE-ConvLSTM-Flow-Dynamics
This repository contains an Auto-encoder ConvLSTM network (Pytorch) which can be used to predict a large number of time steps (100+). The network prediction is sequence-to-sequence which works well to predict 5 to 10-time steps in one pass through the neural network. The network is trained for unsteady fluid simulations using data. Another training method tested is the physics constraint method, where governing equations of fluid motion are used to optimize loss. Few attempts to train unsteady Navier-Stokes are made, but it dint work.
Hzzone/Precipitation-Nowcasting
pytorch implemention of trajGRU.
jhhuang96/ConvLSTM-PyTorch
ConvLSTM/ConvGRU (Encoder-Decoder) with PyTorch on Moving-MNIST
machine-perception-robotics-group/MPRGDeepLearningLectureNotebook
utkuozbulak/pytorch-cnn-visualizations
Pytorch implementation of convolutional neural network visualization techniques
saeedkhaki92/CNN-RNN-Yield-Prediction
This repository contains codes for the paper entitled "A CNN-RNN Framework for Crop Yield Prediction"
totti0223/deep_learning_for_biologists_with_keras
tutorials made for biologists to learn deep learning