Mohammed Oualid Attaoui

Orcid: 0000-0003-3117-9018

According to our database1, Mohammed Oualid Attaoui authored at least 14 papers between 2019 and 2023.

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

Timeline

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PhD thesis 
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Links

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Bibliography

2023
Black-box Safety Analysis and Retraining of DNNs based on Feature Extraction and Clustering.
ACM Trans. Softw. Eng. Methodol., May, 2023

Regions of interest selection in histopathological images using subspace and multi-objective stream clustering.
Vis. Comput., April, 2023

DNN Explanation for Safety Analysis: an Empirical Evaluation of Clustering-based Approaches.
CoRR, 2023

Improved Multi-Objective Data Stream Clustering with Time and Memory Optimization.
Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

2022
Improved Multi-objective Data Stream Clustering with Time and Memory Optimization.
CoRR, 2022

Transfer learning from synthetic labels for histopathological images classification.
Appl. Intell., 2022

Vers de nouvelles méthodes de clustering de flux de données.
Proceedings of the Extraction et Gestion des Connaissances, 2022

2021
Towards new methods of clustering data stream. (Vers de nouvelles méthodes de clustering de flux de données).
PhD thesis, 2021

Subspace data stream clustering with global and local weighting models.
Neural Comput. Appl., 2021

A New Subspace Multi-Objective Approach for the Clustering and Selection of Regions of Interests in Histopathological Images.
Proceedings of the IEEE Congress on Evolutionary Computation, 2021

2020
Multi-objective data stream clustering.
Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020

Soft Subspace Growing Neural Gas pour le Clustering de Flux de Données.
Proceedings of the Extraction et Gestion des Connaissances, 2020

2019
Soft Subspace Topological Clustering over Evolving Data Stream.
Proceedings of the Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization, 2019

Soft Subspace Growing Neural Gas for Data Stream Clustering.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019: Text and Time Series, 2019


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