معرفی
Pierre Poitier is a researcher at the Faculty of Computer Science, Namur Digital Institute (University of Namur), specializing in artificial intelligence applications for sign language recognition and medical imaging. He serves as Project Manager for the SafeTransRNN research project focused on improving temporal segmentation using RNNs with state duration constraints and fuzzy transition modeling.
His research interests span multiple domains of artificial intelligence with emphasis on sign language processing, computer vision, and deep learning applications. His work particularly focuses on data augmentation techniques for contrastive learning, recurrent neural network architectures, transformer models for sign language-to-text translation, and medical image analysis for bronchial carinae detection.
Analysis of his recent publications (2023-2025) reveals a strong research trajectory centered around developing more accurate sign language recognition systems through innovative neural network architectures and data processing techniques. His work demonstrates increasing sophistication from foundational sign language tokenization approaches to more complex contrastive learning frameworks and medical imaging applications.
Dr. Poitier actively collaborates with researchers including Frénay and Fink, and has participated in numerous academic events including the European Symposium on Artificial Neural Networks (ESANN), Intelligent Data Analysis (IDA), and European Conference on Artificial Intelligence (ECAI).
