Peter Naylor

According to our database, Peter Naylor authored at least 11 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Off to new Shores: A Dataset & Benchmark for (near-)coastal Flood Inundation Forecasting.

Brandon Victor, Mathilde Letard, Peter Naylor, Karim Douch, Nicolas Longépé, Zhen He, Patrick Ebel

CoRR, 2024

Implicit neural representation for change detection.

Peter Naylor, Diego Di Carlo, Arianna Traviglia, Makoto Yamada, Marco Fiorucci

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Implicit Assimilation of Sparse In Situ Data for Dense & Global Storm Surge Forecasting.

Patrick Ebel, Brandon Victor, Peter Naylor, Gabriele Meoni, Federico Serva, Rochelle Schneider

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Optimal Transport for Change Detection on Lidar Point Clouds.

Marco Fiorucci, Peter Naylor, Makoto Yamada

Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

2022

Segmentation of Nuclei in Histopathology Images by deep regression of the distance map.

Peter Naylor, Marick Laé, Fabien Reyal, Thomas Walter

Dataset, May, 2022

Scale dependant layer for self-supervised nuclei encoding.

Peter Naylor, Yao-Hung Hubert Tsai, Marick Laé, Makoto Yamada

CoRR, 2022

Feature screening with kernel knockoffs.

Benjamin Poignard, Peter J. Naylor, Héctor Climente-González, Makoto Yamada

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2019

From cellular phenotypes to the analysis of whole slide images: Application to treatment response in triple-negative breast cancer. (Du phénotypage cellulaire à la classification de lames digitales: Une application au traitement du cancer du sein triple-négatif).

Peter Naylor

PhD thesis, 2019

Segmentation of Nuclei in Histopathology Images by Deep Regression of the Distance Map.

Peter Naylor, Marick Lae, Fabien Reyal, Thomas Walter

IEEE Trans. Medical Imaging, 2019

Predicting Residual Cancer Burden In A Triple Negative Breast Cancer Cohort.

Peter Naylor, Joseph Boyd, Marick Laé, Fabien Reyal, Thomas Walter

Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019

2017

Nuclei segmentation in histopathology images using deep neural networks.

Peter Naylor, Marick Lae, Fabien Reyal, Thomas Walter

Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017