luizcoletta Goto Github PK

datasets

Available data for lectures and classes

ext-mask-r-cnn

Python code for Mask R-CNN implementation which provides bounding boxes and segmentation masks on available images.

ext-semantic-segmentation

Python codes implementing deep neural networks for semantic image segmentation

fce-annotation-via-fcm

Python codes (Google Colab) for subimages from an image annotation by using Fuzzy C-Means.

fce-data-fusion

MATLAB code for aerial images feature extraction performing data fusion (old version: https://github.com/luizfsc/fce-remote-sensing)

fce-deep-learning

Python codes to perform semantic segmentation by using deep neural networks

fce-extract-deep-features

Python code for the extraction of deep visual features from aerial images

fce-javamla

JAVA code that allows the use of various supervised and unsupervised machine learning algorithms from WEKA and ELKI libraries

fce-open-world-crop-classification

Python code for detecting and learning new classes of threats present in crops

fce-plant-diseases-recognition

Matlab codes to detection of new patterns (plant diseases) in aerial images from crops

fce-remote-sensing

MATLAB code for feature extraction of aerial images and pattern recognition via clustering and classifiers.

fce-semantic-gan

Adaptation of SemanticGAN presented at CVPR, 2021 (https://nv-tlabs.github.io/semanticGAN/)

fce-vegetation-indices

MATLAB code for the computation of vegetation indices from aerial images.

fce-weed-detection

Python code for the detection of weeds in crops by using Deep Neural Networks.

icmc-c3e

Python implementation of the algorithm C3E (Consensus between Classification and Clustering Ensembles) based on a Squared Loss function (C3E-SL).

luizcoletta.github.io

Personal Website

pgee-crop-images-with-gt

Python codes for cropping images with their corresponding ground truth according to an informed height and width

postach-css