Negin Hayatbini

A Deep Learning Framework for Precipitation Estimation from GOES-16 multispectral satellite imagery - Application of the conditional Generative Adversarial Networks (cGANs)

Negin Hayatbini, Bailey Kong, K. L. Hsu, 2019 .

Spatiotemporal Variations of Precipitation over Iran Using the High-Resolution and Nearly Four Decades Satellite-Based PERSIANN-CDR Dataset

Negin Hayatbini, Soroosh Sorooshian, Mojtaba Sadeghi, 2020, Remote. Sens..

GEONEX: Application of Deep Neural Networks and CloudSat Data in Cloud Type Classification of GOES-16 Multispectral Images for Improving PERSIANN-CCS

Shuang Li, Sangram Ganguly, Ramakrishna R. Nemani, 2018 .

Effective Cloud Detection and Segmentation using a Gradient-Based Algorithm for Satellite Imagery; Application to improve PERSIANN-CCS pdf

Soroosh Sorooshian, Negin Hayatbini, Fuqing Zhang, 2018, Journal of Hydrometeorology.

Conditional Generative Adversarial Networks (cGANs) for Near Real-Time Precipitation Estimation from Multispectral GOES-16 Satellite Imageries - PERSIANN-cGAN

Charless C. Fowlkes, Charless Fowlkes, Negin Hayatbini, 2019, Remote. Sens..

The CHRS Data Portal, an easily accessible public repository for PERSIANN global satellite precipitation data

Kuolin Hsu, Soroosh Sorooshian, Negin Hayatbini, 2019, Scientific Data.

An enhanced artificial neural network with a shuffled complex evolutionary global optimization with principal component analysis

Soroosh Sorooshian, Negin Hayatbini, Tiantian Yang, 2017, Inf. Sci..