Guoexpo

Guoexpo's Stars

• zwhoo/Scale-Sets-Image-Analysis-Toolkit

  Scale-Sets Toolkit for Segmentation of Remote Sensing Images

  7316

• liuxuvip/PolSF

  Language:Python5116

• bminchew/PolarDecomp

  A collection of decomposition routines for polarimetric synthetic aperture radar (PolSAR) applications written in Fortran.

  Language:FORTRAN102

• raktim-ghosh/poldecomp

  Polarimetric Synthetic Aperture Radar (PolSAR) Decomposition Modelling

  Language:Python3111

• aalgo/TSCBPT

  Binary Partition Tree for Polarimetric SAR data

  Language:C++46

• andypbarrett/regrid_piomas

  Wrapper for pyesmf to regrid PIOMAS grids to EASE grids

  Language:Python4

• zmlabe/IceVarFigs

  🌀 Weather and climate graphics for science communication 🌀

  Language:Python8221

• ultralytics/yolov5

  YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

  Language:Python51.1k16.4k

• ShrubHub/GreeningHub

  This is a GitHub repository for 'Complexity revealed in the greening of the Arctic'.

  Language:R810

• davidstutz/superpixels-revisited

  Library containing 7 state-of-the-art superpixel algorithms with a total of 9 implementations used for evaluation purposes in [1] utilizing an extended version of the Berkeley Segmentation Benchmark.

  Language:C++26271

• Bisonai/mobilenetv3-tensorflow

  Unofficial implementation of MobileNetV3 architecture described in paper Searching for MobileNetV3.

  Language:Python22681

• lukasliebel/dfc2020_baseline

  Simple Baseline for the IEEE GRSS Data Fusion Contest 2020

  Language:Python6413

• ZJUGiveLab/UNet-Version

  Language:Python664141

• xcube-dev/xcube

  xcube is a Python package for generating and exploiting data cubes powered by xarray, dask, and zarr.

  Language:Python20319

• asfadmin/AI_Water

  Language:Jupyter Notebook86

• alessandrofrancesconi/gimp-plugin-bimp

  BIMP. Batch Image Manipulation Plugin for GIMP.

  Language:C89493

• w610001795/CNN-SARNet

  Python 2.7.12 : Use Deep Learning (Tensorflow) to classify SAR image, especially for SAR image of ocean

  Language:Python10

• GeomaticsAndRS/sar

  Despeckling Synthetic Aperture Radar Images using a Deep Residual CNN

  Language:Python4316

• xy1377660586/Fine-tuning-a-pre-trained-CNN-for-first-year-sea-ice-and-multi-year-sea-ice-cp-imagery-classificatio

  Mapping first-year sea ice and multi-year sea ice in the oceans is significant for many applications. For example, ship navigation and weather forecast. Accurate and robust classification methods of multi-year ice and first-year ice are in demand [2]. Hybrid-polarity SAR architecture will be included in future SAR missions such as the Canadian RADARSAT Constellation Mission (RCM). These sensors will enable the use of compact polarimetry (CP) data in wide swath imagery [1]. Convolutional neural networks (CNNs) are becoming increasingly popular in many research communities due to availability of large image datasets and high-performance computing systems. As Convolutional networks (ConvNets) have achieved great success on many image classification tasks, I pursue this method for the classification of image patches from compact polarimety (CP) imagery into first-year ice and multi-year ice is applicable. In this course project, my work is kind of like the first practice of the CP imagery classification by fine-tuning a pre-trained convolutional neural network (CNN). Specifically, fine-tuning the last fully-connected layer of a pre-trained convolutional networks, I extract patches from simulated CP images as my dataset, the classification accuracy of the test set achieved 91.3% by fine-tuning a pre-trained CNN, compared to 49.4% classification accuracy by training from scratch.

  Language:Python148

• karmatta/SAR-Satellite_Image_Classification

  Classify SAR-satellite images using CNNs

  Language:Python102

• Jowekk/Dimensionality-reduction-methods

  计算机视觉中的降维方法串烧

  Language:Jupyter Notebook21

• GeorgeSeif/Semantic-Segmentation-Suite

  Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily!

  Language:Python2.5k878

• qubvel/efficientnet

  Implementation of EfficientNet model. Keras and TensorFlow Keras.

  Language:Python2.1k471

• qubvel/segmentation_models

  Segmentation models with pretrained backbones. Keras and TensorFlow Keras.

  Language:Python4.8k1k

• aitorzip/Keras-ICNet

  Keras implementation of Real-Time Semantic Segmentation on High-Resolution Images

  Language:Python8633

• nicolov/segmentation_keras

  DilatedNet in Keras for image segmentation

  Language:Python30192

• mrgloom/awesome-semantic-segmentation

  :metal: awesome-semantic-segmentation

  10.5k2.5k

• nikhilroxtomar/UNet-Segmentation-in-Keras-TensorFlow

  UNet is a fully convolutional network(FCN) that does image segmentation. Its goal is to predict each pixel's class. It is built upon the FCN and modified in a way that it yields better segmentation in medical imaging.

  Language:Jupyter Notebook143112

• zizhaozhang/unet-tensorflow-keras

  A concise code for training and evaluating Unet using tensorflow+keras

  Language:Python18672

• MrGiovanni/UNetPlusPlus

  [IEEE TMI] Official Implementation for UNet++

  Language:Python2.3k541