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Nima Hatami
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2020 – today
- 2024
- [i12]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:
A Robust Ensemble Algorithm for Ischemic Stroke Lesion Segmentation: Generalizability and Clinical Utility Beyond the ISLES Challenge. CoRR abs/2403.19425 (2024) - 2023
- [c13]Nima Hatami, Laura Mechtouff, David Rousseau, Tae-Hee Cho, Omer Faruk Eker, Yves Berthezene, Carole Frindel:
A Novel Autoencoders-LSTM Model for Stroke Outcome Prediction Using Multimodal MRI Data. ISBI 2023: 1-5 - [i11]Nima Hatami:
DeepFEL: Deep Fastfood Ensemble Learning for Histopathology Image Analysis. CoRR abs/2301.09525 (2023) - [i10]Nima Hatami, Laura Mechtouff, David Rousseau, Tae-Hee Cho, Omer Faruk Eker, Yves Berthezene, Carole Frindel:
A Novel Autoencoders-LSTM Model for Stroke Outcome Prediction using Multimodal MRI Data. CoRR abs/2303.09484 (2023) - 2022
- [c12]Nima Hatami, Tae-Hee Cho, Laura Mechtouff, Omer Faruk Eker, David Rousseau, Carole Frindel:
CNN-LSTM Based Multimodal MRI and Clinical Data Fusion for Predicting Functional Outcome in Stroke Patients. EMBC 2022: 3430-3434 - [i9]Nima Hatami, Tae-Hee Cho, Laura Mechtouff, Omer Faruk Eker, David Rousseau, Carole Frindel:
CNN-LSTM Based Multimodal MRI and Clinical Data Fusion for Predicting Functional Outcome in Stroke Patients. CoRR abs/2205.05545 (2022) - 2021
- [i8]Nima Hatami, Mohsin Bilal, Nasir M. Rajpoot:
Deep Multi-Resolution Dictionary Learning for Histopathology Image Analysis. CoRR abs/2104.00669 (2021)
2010 – 2019
- 2019
- [j4]Nima Hatami
Bag of recurrence patterns representation for time-series classification. Pattern Anal. Appl. 22(3): 877-887 (2019) - 2018
- [c11]Nima Hatami, Michaël Sdika, Hélène Ratiney:
Magnetic Resonance Spectroscopy Quantification Using Deep Learning. MICCAI (1) 2018: 467-475 - [i7]Nima Hatami, Yann Gavet, Johan Debayle:
Bag of Recurrence Patterns Representation for Time-Series Classification. CoRR abs/1803.11111 (2018) - [i6]Nima Hatami, Michaël Sdika, Hélène Ratiney:
Magnetic Resonance Spectroscopy Quantification using Deep Learning. CoRR abs/1806.07237 (2018) - 2017
- [c10]Nima Hatami, Yann Gavet
Classification of time-series images using deep convolutional neural networks. ICMV 2017: 106960Y - [i5]Nima Hatami, Yann Gavet, Johan Debayle:
Classification of Time-Series Images Using Deep Convolutional Neural Networks. CoRR abs/1710.00886 (2017) - 2016
- [i4]Nima Hatami, Michael H. Goldbaum:
Automatic Identification of Retinal Arteries and Veins in Fundus Images using Local Binary Patterns. CoRR abs/1605.00763 (2016) - 2013
- [j3]Nima Hatami, Camelia Chira
Diverse accurate feature selection for microarray cancer diagnosis. Intell. Data Anal. 17(4): 697-716 (2013) - [j2]Manuel Graña, Michal Wozniak
Special issue on "Innovative knowledge based techniques in pattern recognition". Pattern Recognit. Lett. 34(14): 1567-1568 (2013) - [c9]Nima Hatami, Camelia Chira
Classifiers with a reject option for early time-series classification. CIEL 2013: 9-16 - [i3]Nima Hatami, Camelia Chira:
Classifiers With a Reject Option for Early Time-Series Classification. CoRR abs/1312.3989 (2013) - [i2]Nima Hatami, Reza Ebrahimpour, Reza Ghaderi:
ECOC-Based Training of Neural Networks for Face Recognition. CoRR abs/1312.3990 (2013) - 2012
- [b1]Nima Hatami:
Some proposals for combining ensemble classifiers. University of Cagliari, Italy, 2012 - [j1]Nima Hatami
Thinned-ECOC ensemble based on sequential code shrinking. Expert Syst. Appl. 39(1): 936-947 (2012) - [c8]Giuliano Armano, Camelia Chira
Ensemble of Binary Learners for Reliable Text Categorization with a Reject Option. HAIS (1) 2012: 137-146 - [c7]Camelia Chira
Hybrid Evolutionary Algorithm with a Composite Fitness Function for Protein Structure Prediction. IDEAL 2012: 184-191 - [c6]Giuliano Armano, Camelia Chira, Nima Hatami:
Error-Correcting Output Codes for Multi-Label Text Categorization. IIR 2012: 26-37 - [i1]Nima Hatami, Camelia Chira, Giuliano Armano:
A Route Confidence Evaluation Method for Reliable Hierarchical Text Categorization. CoRR abs/1206.0335 (2012) - 2011
- [c5]Giuliano Armano, Camelia Chira
A New Gene Selection Method Based on Random Subspace Ensemble for Microarray Cancer Classification. PRIB 2011: 191-201 - [p2]Giuliano Armano, Nima Hatami:
Run-Time Performance Analysis of the Mixture of Experts Model. Computer Recognition Systems 4 2011: 167-175 - [p1]Giuliano Armano
An Improved Mixture of Experts Model: Divide and Conquer Using Random Prototypes. Ensembles in Machine Learning Applications 2011: 217-231 - 2010
- [c4]Giuliano Armano
Mixture of Random Prototype-Based Local Experts. HAIS (1) 2010: 548-556 - [c3]Giuliano Armano
Random Prototype-based Oracle for Selection-fusion Ensembles. ICPR 2010: 77-80
2000 – 2009
- 2008
- [c2]Nima Hatami
Thinned ECOC Decomposition for Gene Expression Based Cancer Classification. ISDA (1) 2008: 216-221 - [c1]Nima Hatami
Error Correcting Output Codes Using Genetic Algorithm-Based Decoding. NCM (1) 2008: 391-396
Coauthor Index
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last updated on 2024-10-07 22:23 CEST by the dblp team
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