Nima Hatami

According to our database, Nima Hatami authored at least 26 papers between 2008 and 2024.

Collaborative distances:

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

2024

A Robust Ensemble Algorithm for Ischemic Stroke Lesion Segmentation: Generalizability and Clinical Utility Beyond the ISLES Challenge.

Ezequiel de la Rosa, Mauricio Reyes, Sook-Lei Liew, Alexandre Hutton, Roland Wiest, Johannes Kaesmacher, Uta Hanning, Arsany Hakim, Richard Zubal, Waldo Valenzuela, David Robben, Diana Maria Sima, Vincenzo Anania, Arne Brys, James A. Meakin, Anne Mickan, Gabriel Broocks, Christian Heitkamp, Shengbo Gao, Kongming Liang, Ziji Zhang, Md Mahfuzur Rahman Siddiquee, Andriy Myronenko, Pooya Ashtari, Sabine Van Huffel, Hyun-su Jeong, Chiho Yoon, Chulhong Kim, Jiayu Huo, Sébastien Ourselin, Rachel Sparks, Albert Clèrigues, Arnau Oliver, Xavier Lladó, Liam F. Chalcroft, Ioannis Pappas, Jeroen Bertels, Ewout Heylen, Juliette Moreau, Nima Hatami, Carole Frindel, Abdul Qayyum, Moona Mazher, Domenec Puig, Shao-Chieh Lin, Chun-Jung Juan, Tianxi Hu, Lyndon Boone, Maged Goubran, Yi-Jui Liu, Susanne Wegener, Florian Kofler, Ivan Ezhov, Suprosanna Shit, Moritz Roman Hernandez Petzsche, Bjoern H. Menze, Jan S. Kirschke, Benedikt Wiestler

CoRR, 2024

2023

DeepFEL: Deep Fastfood Ensemble Learning for Histopathology Image Analysis.

Nima Hatami

CoRR, 2023

A Novel Autoencoders-LSTM Model for Stroke Outcome Prediction Using Multimodal MRI Data.

Nima Hatami, Laura Mechtouff, David Rousseau, Tae-Hee Cho, Omer Faruk Eker, Yves Berthezene, Carole Frindel

Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

2022

CNN-LSTM Based Multimodal MRI and Clinical Data Fusion for Predicting Functional Outcome in Stroke Patients.

Nima Hatami, Tae-Hee Cho, Laura Mechtouff, Omer Faruk Eker, David Rousseau, Carole Frindel

Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

2021

Deep Multi-Resolution Dictionary Learning for Histopathology Image Analysis.

Nima Hatami, Mohsin Bilal, Nasir M. Rajpoot

CoRR, 2021

2019

Bag of recurrence patterns representation for time-series classification.

Nima Hatami, Yann Gavet, Johan Debayle

Pattern Anal. Appl., 2019

2018

Magnetic Resonance Spectroscopy Quantification Using Deep Learning.

Nima Hatami, Michaël Sdika, Hélène Ratiney

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

2017

Classification of time-series images using deep convolutional neural networks.

Nima Hatami, Yann Gavet, Johan Debayle

Proceedings of the Tenth International Conference on Machine Vision, 2017

2016

Automatic Identification of Retinal Arteries and Veins in Fundus Images using Local Binary Patterns.

Nima Hatami, Michael H. Goldbaum

CoRR, 2016

2013

Special issue on "Innovative knowledge based techniques in pattern recognition".

Manuel Graña, Michal Wozniak, Nima Hatami

Pattern Recognit. Lett., 2013

Diverse accurate feature selection for microarray cancer diagnosis.

Nima Hatami, Camelia Chira

Intell. Data Anal., 2013

ECOC-Based Training of Neural Networks for Face Recognition.

Nima Hatami, Reza Ebrahimpour, Reza Ghaderi

CoRR, 2013

Classifiers with a reject option for early time-series classification.

Nima Hatami, Camelia Chira

Proceedings of the IEEE Symposium on Computational Intelligence and Ensemble Learning, 2013

2012

Some proposals for combining ensemble classifiers.

Nima Hatami

PhD thesis, 2012

Thinned-ECOC ensemble based on sequential code shrinking.

Nima Hatami

Expert Syst. Appl., 2012

A Route Confidence Evaluation Method for Reliable Hierarchical Text Categorization

Nima Hatami, Camelia Chira, Giuliano Armano

CoRR, 2012

Error-Correcting Output Codes for Multi-Label Text Categorization.

Giuliano Armano, Camelia Chira, Nima Hatami

Proceedings of the 3rd Italian Information Retrieval Workshop, 2012

Hybrid Evolutionary Algorithm with a Composite Fitness Function for Protein Structure Prediction.

Camelia Chira, Nima Hatami

Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2012, 2012

Ensemble of Binary Learners for Reliable Text Categorization with a Reject Option.

Giuliano Armano, Camelia Chira, Nima Hatami

Proceedings of the Hybrid Artificial Intelligent Systems - 7th International Conference, 2012

2011

An Improved Mixture of Experts Model: Divide and Conquer Using Random Prototypes.

Giuliano Armano, Nima Hatami

Proceedings of the Ensembles in Machine Learning Applications, 2011

Run-Time Performance Analysis of the Mixture of Experts Model.

Giuliano Armano, Nima Hatami

Proceedings of the Computer Recognition Systems 4, 2011

A New Gene Selection Method Based on Random Subspace Ensemble for Microarray Cancer Classification.

Giuliano Armano, Camelia Chira, Nima Hatami

Proceedings of the Pattern Recognition in Bioinformatics, 2011

2010

Random Prototype-based Oracle for Selection-fusion Ensembles.

Giuliano Armano, Nima Hatami

Proceedings of the 20th International Conference on Pattern Recognition, 2010

Mixture of Random Prototype-Based Local Experts.

Giuliano Armano, Nima Hatami

Proceedings of the Hybrid Artificial Intelligence Systems, 5th International Conference, 2010

2008

Error Correcting Output Codes Using Genetic Algorithm-Based Decoding.

Nima Hatami, Saeed Seyedtabaii

Proceedings of the NCM 2008, The Fourth International Conference on Networked Computing and Advanced Information Management, Gyeongju, Korea, September 2-4, 2008, 2008

Thinned ECOC Decomposition for Gene Expression Based Cancer Classification.

Nima Hatami

Proceedings of the Eighth International Conference on Intelligent Systems Design and Applications, 2008