Home › Researcher directory › Hanane Azzag
Hanane Azzag
Affiliation : Centre National de la Recherche Scientifique · Université Sorbonne Paris Nord · Laboratoire d'Informatique de Paris-Nord
- 24Publications (affiliation in France)
- 216Total publications
- 928Citations
- 16h-index
Research profile
Hanane Azzag has 24 indexed publications (2015–2026). Their work appears mainly in “arXiv (Cornell University)”, “HAL” and “Neural Computing and Applications”. Their most cited article, “Transfer learning from synthetic labels for histopathological images classification” (2021), has been cited 27 times. 12 of these publications date from the last three years of activity. Their work is co-authored with at least 12 researchers, including institutions in Algeria, Tunisia.
Is this you? Get your research seen
Create your free DzCademia profile and add your articles: they will show up more easily on Google and in AI assistants like ChatGPT, so more people can read and cite your work.
Create my free profile Add my publicationsResearch areas
- Advanced Clustering Algorithms Research
- Data Visualization and Analytics
- Neural Networks and Applications
- Data Mining and Machine Learning Applications
- Metaheuristic Optimization Algorithms Research
Publications (24)
- Game Theory Meets Statistical Physics: A Novel Deep Neural Networks Design
- NeuroGame Transformer: Gibbs-Inspired Attention Driven by Game Theory and Statistical Physics
- A Collective Variational Principle Unifying Bayesian Inference, Game Theory, and Thermodynamics
- Coalition Free Energy and Adaptive Precision in Multi-Agent Cooperation
- MonoASR: un modèle de reconnaissance vocale multilingue frugal et unifié
- LoRA-ASR: A Parameter-Efficient and Scalable Model for Multilingual ASR
- Redesigning deep neural networks: Bridging game theory and statistical physics
- OneEncoder: a lightweight framework for efficient multimodal training
- Distributed Collapsed Gibbs Sampler for Dirichlet Process Mixture Models in Federated Learning
- Lightweight Cross-Modal Representation Learning
- Adaptative Context Normalization: A Boost for Deep Learning in Image Processing
- Game Theory Meets Statistical Mechanics in Deep Learning Design
- Context Normalization Layer with Applications
- Regions of interest selection in histopathological images using subspace and multi-objective stream clustering
- Transfer learning from synthetic labels for histopathological images classification
- A New Subspace Multi-Objective Approach for the Clustering and Selection of Regions of Interests in Histopathological Images
- Subspace data stream clustering with global and local weighting models
- Soft Subspace Growing Neural Gas for Data Stream Clustering
- Soft Subspace Topological Clustering over Evolving Data Stream
- An ant-based new clustering model for graph proximity construction
- A Distributed Rough Set Theory Algorithm based on Locality Sensitive Hashing for an Efficient Big Data Pre-processing
- CL-AntInc Algorithm for Clustering Binary Data Streams Using the Ants Behavior
- How to use ants for data stream clustering
- Clustering of Binary Data Sets Using Artificial Ants Algorithm
Publication venues
- arXiv (Cornell University) × 3
- HAL × 3
- Neural Computing and Applications × 2
- IEEE Congress on Evolutionary Computation (CEC) × 2
- Lecture notes in computer science × 2
- IEEE Transactions on Cybernetics × 1
Publications per year
- 20266
- 20252
- 20244
- 20231
- 20221
- 20212
- 20201
- 20193
- 20181
- 20161
Collaborations
Partner institutions : Données et algorithmes pour une ville intelligente et durable · Université de Versailles Saint-Quentin-en-Yvelines · Université Paris-Saclay · Laboratoire d'Informatique, du Traitement de l'Information et des Systèmes · University of Sfax
Co-authors’ countries : Algeria · Tunisia
Co-authors
- Mustapha Lebbah
- Bilal Faye
- Mohammed Oualid Attaoui
- Djamel Bouchaffra
- Nesrine Masmoudi
- Cyrille Bertelle
- Ilyes Oukid
- Mohammed Ghesmoune
- Mustapha Lebbah
- Cyrille Bertelle
- Djamel Bouchaffra
- Djamel Bouchaffra
Bibliographic data from OpenAlex (open database).
Why choose Dzcademia?
Profiles, articles and conference contributions: give your research a structured public presence. Integrated metadata help search engines and AI assistants identify your work and understand its references.
Comment with Google
Sign in with Google to comment directly on this page.