Search Results for author: Alberto Todeschini

Found 7 papers, 3 papers with code

Upscaling Global Hourly GPP with Temporal Fusion Transformer (TFT)

no code implementations23 Jun 2023 Rumi Nakagawa, Mary Chau, John Calzaretta, Trevor Keenan, Puya Vahabi, Alberto Todeschini, Maoya Bassiouni, Yanghui Kang

Prior machine learning studies on upscaling \textit{in situ} GPP to global wall-to-wall maps at sub-daily time steps faced limitations such as lack of input features at higher temporal resolutions and significant missing values.

Feature Importance Time Series

Snowpack Estimation in Key Mountainous Water Basins from Openly-Available, Multimodal Data Sources

1 code implementation8 Aug 2022 Malachy Moran, Kayla Woputz, Derrick Hee, Manuela Girotto, Paolo D'Odorico, Ritwik Gupta, Daniel Feldman, Puya Vahabi, Alberto Todeschini, Colorado J Reed

Accurately estimating the snowpack in key mountainous basins is critical for water resource managers to make decisions that impact local and global economies, wildlife, and public policy.

Deep Learning-Based Acoustic Mosquito Detection in Noisy Conditions Using Trainable Kernels and Augmentations

1 code implementation28 Jul 2022 Devesh Khandelwal, Sean Campos, Shwetha Nagaraj, Fred Nugen, Alberto Todeschini

In this paper, we demonstrate a unique recipe to enhance the effectiveness of audio machine learning approaches by fusing pre-processing techniques into a deep learning model.

SunCast: Solar Irradiance Nowcasting from Geosynchronous Satellite Data

no code implementations17 Jan 2022 Dhileeban Kumaresan, Richard Wang, Ernesto Martinez, Richard Cziva, Alberto Todeschini, Colorado J Reed, Hossein Vahabi

Accurate short-term PV power prediction enables operators to maximize the amount of power obtained from PV panels and safely reduce the reserve energy needed from fossil fuel sources.

HyperionSolarNet: Solar Panel Detection from Aerial Images

1 code implementation6 Jan 2022 Poonam Parhar, Ryan Sawasaki, Alberto Todeschini, Colorado Reed, Hossein Vahabi, Nathan Nusaputra, Felipe Vergara

The energy sector is the single largest contributor to climate change and many efforts are focused on reducing dependence on carbon-emitting power plants and moving to renewable energy sources, such as solar power.

Segmentation Semantic Segmentation

Self-supervised Contrastive Learning for Irrigation Detection in Satellite Imagery

no code implementations12 Aug 2021 Chitra Agastya, Sirak Ghebremusse, Ian Anderson, Colorado Reed, Hossein Vahabi, Alberto Todeschini

Climate change has caused reductions in river runoffs and aquifer recharge resulting in an increasingly unsustainable crop water demand from reduced freshwater availability.

Contrastive Learning

High-resolution global irrigation prediction with Sentinel-2 30m data

no code implementations9 Dec 2020 Weixin, Wu, Sonal Thakkar, Will Hawkins, Puya Vahabi, Alberto Todeschini

An accurate and precise understanding of global irrigation usage is crucial for a variety of climate science efforts.

Clustering Vocal Bursts Intensity Prediction

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