CNN-SoilTextureClassification
Soil classifier
A framework for training and utilizing 1D CNN models for soil texture classification from hyperspectral data
1-dimensional convolutional neural networks (CNN) for the classification of soil texture based on hyperspectral data
58 stars
4 watching
16 forks
Language: Python
last commit: over 4 years agoLinked from 1 awesome list
1d-cnnclassificationcnnconferenceconvolutional-neural-networkshyperspectral-datapublicationpublication-codesoil-texture-classification
Related projects:
| Repository | Description | Stars |
|---|---|---|
| Provides hyperspectral and soil-moisture data from a field campaign | 43 | |
| A package providing tools to classify and analyze soil texture based on soil particle size distribution. | 28 | |
| Developing Deep Learning models for classifying land covers in hyperspectral images using Neural Networks | 298 | |
| A deep learning framework for training highway networks on image data using convolutional neural networks | 57 | |
| An implementation of Kim's Convolutional Neural Networks for Sentence Classification in PyTorch | 1,022 | |
| Automated high-throughput root phenotyping platform using image processing and machine learning algorithms. | 25 | |
| A dataset and model for predicting soil properties and classes at high spatial resolution using machine learning and remote sensing data. | 35 | |
| Matlab implementation of a deep learning-based method for classifying hyperspectral images | 56 | |
| Classifies high-resolution microscopy images of lung adenocarcinoma using deep neural networks with a sliding window framework. | 494 | |
| A software framework implementing Deformable Convolutional Networks for object detection and image segmentation tasks | 160 | |
| An implementation of convolutional neural networks for text classification using PyTorch | 66 | |
| Automates XRD pattern classification using CNNs and data augmentation | 50 | |
| Developing and evaluating deep learning models for time series classification with a focus on interpretability and deployability. | 682 | |
| An implementation of a deep learning model for tree species classification from hyperspectral images | 120 | |
| A PyTorch project for comparing image classification models and facilitating quick experiment setup | 366 |