FOCUS on Contamination: A Geospatial Deep Learning Framework with a Noise-Aware Loss for Surface Water PFAS Prediction

17 February 2025

Papers citing "FOCUS on Contamination: A Geospatial Deep Learning Framework with a Noise-Aware Loss for Surface Water PFAS Prediction"

9 / 9 papers shown

Title
How accurate are existing land cover maps for agriculture in Sub-Saharan Africa? Hannah Kerner C. Nakalembe Adam X. Yang Ivan Zvonkov Ryan McWeeny Gabriel Tseng I. Becker-Reshef 25 15 0 05 Jul 2023
SatMAE: Pre-training Transformers for Temporal and Multi-Spectral Satellite Imagery Yezhen Cong Samarth Khanna Chenlin Meng Patrick Liu Erik Rozi Yutong He Marshall Burke David B. Lobell Stefano Ermon ViT 44 264 0 17 Jul 2022
Generalized Huber Loss for Robust Learning and its Efficient Minimization for a Robust Statistics Kaan Gokcesu Hakan Gokcesu 75 59 0 28 Aug 2021
Semantic Segmentation of Remote Sensing Images with Sparse Annotations Yuansheng Hua Diego Marcos Lichao Mou Xiaoxiang Zhu D. Tuia 73 81 0 10 Jan 2021
Human-Machine Collaboration for Fast Land Cover Mapping Caleb Robinson Anthony Ortiz Kolya Malkin Blake Elias Andi Peng Dan Morris B. Dilkina Nebojsa Jojic 46 20 0 10 Jun 2019
Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels Zhilu Zhang M. Sabuncu NoLa 48 2,580 0 20 May 2018
On Calibration of Modern Neural Networks Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger UQCV 133 5,774 0 14 Jun 2017
XGBoost: A Scalable Tree Boosting System Tianqi Chen Carlos Guestrin 131 37,815 0 09 Mar 2016
Training Deep Neural Networks on Noisy Labels with Bootstrapping Scott E. Reed Honglak Lee Dragomir Anguelov Christian Szegedy D. Erhan Andrew Rabinovich NoLa 84 1,014 0 20 Dec 2014