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neha742's Projects

change-detection-in-satellite-imagery icon change-detection-in-satellite-imagery

It employes Principal Component Analysis (PCA) and K-means clustering techniques over difference image to detect changes in multi temporal images satellite imagery.

change-detection-review icon change-detection-review

A review of change detection methods, including codes and open data sets for deep learning. From paper: change detection based on artificial intelligence: state-of-the-art and challenges.

fuzzy-dbscan icon fuzzy-dbscan

Modifiying DBSCAN clustering algorithm with addition of fuzziness

ga_project_4_advanced_supervised_unsupervised_learning icon ga_project_4_advanced_supervised_unsupervised_learning

GA Project 4: Using Advanced Supervised Learning models e.g. (Extreme) Gradient Boosting Trees and Random Forest Classifier models, as well as Unsupervised Learning models e.g. DBSCAN, K-Means Clustering. Working with geospatial, categorical and numerical data in the West Nile Virus dataset. Groupwork setting with my peers Evonne and Rong - based on github collaboration best practices.

hyperspectral-image-classification- icon hyperspectral-image-classification-

This Dataset contains the complete datacube collected from the Salinas scene. where hyperspectral data measures can be implemented on These is the scene acquired by the AVIRIS sensor during flight campaign over Salinas Valley, California. The number of spectral band is 203 for Salinas scene. Salinas scene is 512*512 pixels. 217 Samples in the images contain no information and have to be described before the analysis. The geometric resolution is 3.7 meters. Image ground truths differentiate 16 classes each.

neha742 icon neha742

Config files for my GitHub profile.

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