Saeed Izadi

According to our database1, Saeed Izadi authored at least 13 papers between 2015 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2023
AmberTools.
J. Chem. Inf. Model., October, 2023

Image denoising in the deep learning era.
Artif. Intell. Rev., 2023

2021
D-LEMA: Deep Learning Ensembles From Multiple Annotations - Application to Skin Lesion Segmentation.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

AECNN: Adversarial and Enhanced Convolutional Neural Networks.
Proceedings of the Computer-Aided Analysis of Gastrointestinal Videos, 2021

2020
Patch-Based Non-local Bayesian Networks for Blind Confocal Microscopy Denoising.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

2019
Image Super Resolution via Bilinear Pooling: Application to Confocal Endomicroscopy.
Proceedings of the Machine Learning for Medical Image Reconstruction, 2019

WhiteNNer-Blind Image Denoising via Noise Whiteness Priors.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

2018
Can Deep Learning Relax Endomicroscopy Hardware Miniaturization Requirements?
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

Deep auto-context fully convolutional neural network for skin lesion segmentation.
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018

Generative adversarial networks to segment skin lesions.
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018

2017
Grid-Based Surface Generalized Born Model for Calculation of Electrostatic Binding Free Energies.
J. Chem. Inf. Model., October, 2017

2016
iLab-20M: A Large-Scale Controlled Object Dataset to Investigate Deep Learning.
Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015
What can we learn about CNNs from a large scale controlled object dataset?
CoRR, 2015


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