Call For Papers

The call for paper and the platform to submit your paper will be announced soon.

ANNPR 2026 invites papers that present original work in the areas of neural networks and machine learning oriented to pattern recognition,
focusing on their algorithmic, theoretical, and applied aspects. Topics of interest include, but are not limited to:

   Methodological Issues
     – Supervised, semi-supervised, unsupervised, and reinforcement learning
     – Deep learning and deep reinforcement learning
     – Feed-forward, recurrent, and convolutional neural networks
     – Hierarchical modular architectures and hybrid systems
     – Interpretability and explainability of neural networks
     – Generative models
     – Robustness & generalization of neural networks
     – Meta-learning, Auto-ML
     – Multiple classifier systems and ensemble methods
     – Kernel machines
     – Probabilistic graphical models

   Applications to Pattern Recognition
     – Image processing and segmentation
     – Object detection
     – NLP and conversational agents
     – Sensor-fusion and multi-modal processing
     – Biometrics, including sspeech and speaker recognition and segmentation
     – Data, text, and social media analytics
     – Bioinformatics/Cheminformatics and medical applications
     – Industrial applications, e.g. quality control and predictive maintenance
     – Data clustering